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Retrospective performance evaluation of a computer-aided detection (CAD) system on standard posteroanterior (PA) chest radiographs (PA-CXR) in detection of pulmonary nodules, infectious consolidation, pneumothorax, pleural effusion, aortic calcification, cardiomegaly and rib fractures compared to radiologists analyzing PA-CXR including dual-energy subtraction radiography (further termed as DESR).PA-CXR/DESR images of 197 patients were included. All patients underwent chest CT (gold standard) within a short interval (mean 28 hours). All images were evaluated by three blinded readers for the presence of pulmonary nodules, infectious consolidation, pneumothorax, pleural effusion, aortic calcification, cardiomegaly, and rib fractures. Meanwhile PA-CXR were analyzed by a CAD software. CAD results were compared to the majority result of the three readers. Sensitivity and specificity were calculated. McNemar's test was applied to test for significant differences. Interobserver agreement was defined using Cohen's kappa (κ).Sensitivity of the CAD software was significantly higher (p0.05) for detection of infectious consolidation and pulmonary nodules (67.9% vs 26.8% and 54% vs 35.6%, respectively; p0.001) compared to radiologists analyzing DESR images. For the residual evaluated pathologies no statistical significant differences could be found. Overall, mean inter observer agreement between the three radiologists was moderate (k = 0.534). The best interobserver agreement could be reached for pneumothorax (k = 0.708) and pleural effusion (k = 0.699), while the worst was obtained for rib fractures (k = 0.412).The CAD system has the potential to improve the detection of infectious consolidation and pulmonary nodules on CXR images.

The assessment and diagnosis of agricultural drought vulnerability is the basis for the scientific control and prevention of agricultural drought risk. In order to quantitatively evaluate the regional agricultural drought vulnerability and effectively deal with the fuzziness and randomness between evaluation sample and evaluation grade, the entropy fuzzy pattern recognition model, which was coupled with maximum information entropy principle and fuzzy pattern recognition method, was applied to the evaluation of agricultural drought vulnerability. Furthermore, in order to find methods to reduce drought vulnerability, the subtraction set pair potential method was used to further identify the main influence factors of agricultural drought vulnerability. In addition, a case study was carried out in Bengbu City, China. The results showed that during the period from 2001 to 2010, the evaluation value of agricultural drought vulnerability in Bengbu dropped from grade IV to III, which meant that the tolerance of agricultural system to drought had been improved. Moreover, the main factors that affected the vulnerability in Bengbu were precipitation, water use efficiency and irrigation protection area rate. And the latter two were the main objects of regulation and control. Compared with the other three methods, the physical concept of drought vulnerability assessment model based on entropy fuzzy pattern recognition is more obvious, and the evaluation results are reasonable and credible. The drought vulnerability diagnosis method based on subtraction set pair potential can accurately identify key influence factor and provide measures to reduce drought vulnerability and improve drought risk management.

Ground-penetrating radar (GPR) is a well-known geophysical electromagnetic method used to detect the underground facilities such as landmines, pipelines, and cavities. In general, the clutter presented in GPR B-scan image obscures the underground objects, thus damaging the performance of the underground object detection algorithm. In this letter, we proposed a new clutter suppression method based on robust autoencoder (RAE). The proposed algorithm decomposes a GPR B-scan image into its low-rank and sparse components. The low-rank component catches the clutter, whereas the sparse component captures the underground object responses. The commonly used clutter removal algorithms, mean subtraction (MS), singular value decomposition (SVD), robust principal component analysis (RPCA), and morphological component analysis (MCA), are compared with the proposed algorithm on both the numerical simulated data and real GPR data. The visual and quantitative results demonstrate the effectiveness of the proposed RAE-based algorithm over the widely used state-of-the-art clutter removal algorithms.

BACKGROUND Acute gastrointestinal bleeding (GIB) is a life-threatening medical emergency with high morbidity and mortality. Transcatheter embolization with endovascular coils under digital subtraction angiography guidance is a common and effective method for the treatment of GIB with high technical success rates. Duodenal ulcers caused by coils wiggled from the branch of the gastroduodenal artery, which is a rare complication, have not previously been reported in a patient with right intrathoracic stomach. CASE SUMMARY A 62-year-old man had undergone thoracoscopy-assisted radical resection of esophageal cancer and gastroesophageal anastomosis 3 years ago, resulting in right intrathoracic stomach. He was admitted to the hospital 15 mo ago for dizziness and suffered acute GIB during his stay. Interventional surgery was urgently performed to embolize the branch of the gastroduodenal artery with endovascular coils. After 15 mo, the patient was re-admitted with a chief complaint of melena for 2 d, esophagogastroduodenoscopy and abdominal computed tomography revealed that some endovascular coils had migrated into the duodenal bulb, leading to a deep ulcer. Bleeding was controlled after conservative treatment. Seven months later, duodenal balloon dilatation was performed to relieve the stenosis after the removal of a few coils, and the patient was safely discharged with only one coil retained in the duodenum due to difficulties in complete removal and risk of bleeding. Mild melena recurred once during the long-term follow-up. CONCLUSION Although rare, coil wiggle after interventional therapy requires careful attention, effective precautionary measures, and more secure alternative treatment methods.

13N-ammonia and 18F-flurpiridaz require longer delays between rest and stress studies to allow for decay, lowering clinical throughput. In this study, we investigated the impact of residual subtraction on MBF and MFR estimates, as well as its effects on diagnostic accuracy. We retrospectively analyzed 63 patients who underwent a dynamic ammonia rest/stress study and 231 patients from the flurpiridaz 301 trial. Residual subtraction was performed by subtracting the mean pre-injection activity in each sampled region from that region’s time activity curve. Corrected and uncorrected MBF and MFR were analyzed. Diagnostic accuracy was compared to quantitative coronary angiograms (QCA) for the flurpiridaz population. With delays between injections above 3 half-lives, and a doubled stress dose, residual activity did not meaningfully increase ammonia MBF (

Background The modified thrombolysis in cerebral infarction (mTICI) scale is a widely used and validated qualitative tool to evaluate angiographic intracerebral inflow following endovascular thrombectomy (EVT). We validated a machine-learning (ML) algorithm to grade digital subtraction angiograms (DSA) using the mTICI scale. Materials and methods We included angiograms of identified middle cerebral artery (MCA) occlusions who underwent EVT. The complete DSA sequences were preprocessed and normalized. We created three convolutional neural networks to classify DSA into two outcomes, low- (mTICI 0,1,2a) and high-grade (mTICI 2b,2c,3). Results We included a total of 234 angiograms in this study. The area under the receiver operating characteristic was 0.863 (95% CI 0.816-0.909), 0.914 (95% CI 0.876-0.951), and 0.890 (95% CI 0.848-0.932) for the anteroposterior (AP), lateral (L), and combined models, respectively, when dichotomizing outcomes into low and high grade. The models' area under the precision-recall curve was 0.879 (95% CI 0.829-0.930), 0.906 (95% CI 0.844-0.968), and 0.887 (95% CI 0.834-0.941) for the AP, L, and combined models. Conclusion In complete cerebral DSA, our angiography-based ML strategy was able to predict mTICI scores following EVT rapidly and reliably for MCA occlusions.

Background Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide, and if left untreated, one of the most lethal. Ablative therapies including radiofrequency ablation (RFA) play increasingly important role for patients with liver tumors who are not surgical candidates. Monitoring treatment response following ablation is crucial in oncologic imaging. Dynamic contrast-enhanced MRI can assess changes in tumor vascularity and perfusion while subtraction imaging is useful in differentiating residual tumor from post-ablation parenchymal changes. The aim of this study is to compare the role of subtraction MRI and conventional dynamic MRI in assessing treatment response following RFA in patients with HCC. Results The study included 48 patients with 62 HCC lesions who underwent RFA from May to October 2020, followed by MRI evaluation with 1-month interval. Two readers with experience in hepatic imaging interpreted the dynamic and subtraction dynamic MRI. The hepatic focal lesions were classified into “well-ablated” and “residual” groups according to MRI findings, and the agreement between the two readers was evaluated. Using dynamic MRI, the first reader reported 38 well-ablated lesions, and the second reader agreed in 34 of them (89.5%). Residual disease was reported by the first reader in 22 lesions and the second reader disagreed in 10 of them (45.5%) where complete ablation was reported. Thirty-eight out 44 well-ablated lesions (86.4%) showed high signal intensity on non-enhanced T1 images, and 28 lesion (63.6%) showed intermediate T2 signal. All the mis-matched readings occurred in lesions with a high signal intensity in pre-contrast T1 images. Moderate agreement between the two readers was found with Kappa value of 0.467. Significant additive value of subtraction technique to dynamic MRI was detected with a P value of 0.009. No major complications recorded except for a single case of major portal vein branch occlusion. Conclusion MRI is a powerful imaging tool in assessing tumor viability and complications after RFA in patients with HCC. Dynamic MRI study is the gold standard in detecting recurrent lesions while subtraction technique is crucial in differentiating between arterial enhancement due to residual disease and normal hyperintense T1 signal of the ablation zone.

Vehicle segmentation, traffic density estimation and vehicle tracking are some of the important functionalities in smart traffic management. Segmentation of vehicles from traffic surveillance videos can help to realize many applications like speed monitoring, traffic estimation etc. Vehicle segmentation from surveillance videos becomes very challenging due to presence of occlusions, cluttered backgrounds and traffic density variations. In this work, we propose a deep learning adapted active net segmentation model for vehicle segmentation. The proposed solution involves three stages: adaptive background model based subtraction, active net sub netting with CNN, refined from CNN results with ETAN optimization. Adaptive background modeling is based on an adaptive gain function which is constructed from the pixels of the frames in the video. The gain function is able to compensate for the shadow and illumination problems affecting the vehicle segmentation. Deep learning assisted topological active net deformable model is able to provide higher segmentation accuracy in presence of occlusions, cluttered backgrounds and traffic density variations.

In this paper, a color image encryption algorithm based on Fisher-Yates scrambling and DNA subsequence operation (elongation operation, truncation operation, deletion operation, insertion arithmetic) is proposed. Firstly, the three-dimensional color image is transformed into two-dimensional gray image, and the chaotic sequence generated by Chen system and Fisher-Yates scrambling method is used to scramble the plaintext images of R, G and B channels. Secondly, the three channel images of the scrambled plaintext image are transformed into three DNA sequence matrixes by using the DNA coding rules, and then the three DNA sequence matrixes are manipulated by using DNA subsequence operation and DNA addition, subtraction and XOR operation to destroy the scrambled plaintext information. Finally, the color encrypted image is obtained by using the DNA decoding rule. Experimental results and security analysis demonstrate that our encryption algorithm has good performance and may resist against various typical attacks.

Purpose The purpose of this study was to investigate the usefulness of temporal subtraction CT (TSCT) of temporal bone CT for the detection of postoperative recurrent/residual cholesteatoma of the middle ear. Methods Thirty-two consecutive patients with surgically proven postoperative recurrent/residual cholesteatoma and 14 consecutive patients without recurrent/residual lesion matched the selection criteria and were retrospectively evaluated. TSCT imaging was generated with the use of serial postoperative CT. Two experienced radiologists and two residents evaluated the presence of bone erosive change by comparison serial CT studies, and CT and TSCT. The detection rate of bone erosive change, sensitivity and specificity of the recurrence/residual lesions, and reading time for each reader were evaluated. Results TSCT + CT significantly improved the detection of bone erosive changes compared to CT-only evaluation (17.4–41.3% vs. 37.0–58.7%, p = 0.008–0.046). The mean sensitivity and specificity of TSCT + CT for experienced radiologists were 0.77 and 1.00, and 0.52 and 0.97 without TSCT. The mean sensitivity and specificity of TSCT + CT for residents were 0.64 and 1.00, and 0.41 and 1.00 without TSCT. Sensitivity showed an increase in all readers. The use of TSCT significantly reduced the reading time per case in all readers (p Conclusion TSCT improves the depiction of newly occurring progressive bone erosive changes, and detection sensitivity and reading time in postoperative recurrence/residual cholesteatoma of middle ear.

Study design Experimental study. Objectives The goal of this study was to develop a 3D-printed pedicle subtraction osteotomy (PSO) guide plate system. A 3D model and postoperative CT data were used to evaluate the accuracy of osteotomy with this system. Summary of background data The key to the success of spinal orthopaedic treatment is an effectively performed osteotomy. A 3D-printed osteotomy plate can be used for preoperative surgical planning. Due to the anatomical complexity of the spinal region, the clinical application of 3D-printed osteotomy plates remains challenging. Methods The CT scans of 10 patients with thoracolumbar spinal deformities were obtained in the DICOM format. The diseased vertebrae and adjacent vertebrae were reconstructed and reduced by computer-aided design (CAD) software, and an osteotomy plate was designed for the diseased vertebrae. The 3D-printed spinal model and osteotomy plate were used to simulate the operation for PSO. After the operation, the vertebral body treated by osteotomy underwent a CT scan, and the findings were compared with the preoperative design to evaluate the osteotomy accuracy. Results The new 3D guide plate and spine model were used to successfully simulate 10 cases of PSO, and the comparison of the preoperative and postoperative states indicated that the osteotomy outcomes were excellent. Conclusions The new 3D-printed PSO guide plate system can be used for preoperative osteotomy planning and demonstrates good accuracy. The results can be used to develop 3D-printed plans for PSO in clinical practice.Level of Evidence: 3.

Previously, a joint ictal/inter-ictal SPECT reconstruction was proposed to reconstruct a differential image representing the change of brain SPECT image from an inter-ictal to an ictal study. The so-called joint method yielded better performance for epileptic foci localization than the conventional subtraction method. In this study, we evaluated the performance of different reconstruction settings of the joint reconstruction of ictal/inter-ictal SPECT data, which creates a differential image showing the difference between ictal and inter-ictal images, in lesion detection and localization in epilepsy imaging. Differential images reconstructed from phantom data using the joint and the subtraction methods were compared based on lesion detection performance (channelized Hotelling observer signal-to-noise ratio (SNRCHO) averaged across four lesion-to-background contrast levels) at the optimal iteration. The joint-initial method which was the joint method that was initialized by the subtraction method at optimal iteration was also used to reconstruct differential images. These three methods with respective optimal iteration and the subtraction method with four iterations were applied to epileptic patient datasets. A human observer lesion localization study was performed based on localization receiver operating characteristic (LROC) analysis. From the phantom study, at their respective optimal iteration, the joint method yielded an improvement in lesion detection performance over the subtraction method of 26%, which increased to 145% when using the joint-initial method. From the patient study, the joint-initial method yielded the highest area under the LROC curve as compared with those of the joint and the subtraction methods with optimal iteration and with 4 iterations (0.44 vs 0.41, 0.39 and 0.36, respectively). In lesion detection and localization, the joint method at optimal iteration outperformed the subtraction method at optimal iteration and at iteration typically used in clinical practice. Furthermore, initialization by the subtraction method improved the performance of the joint method.

The data quality of simultaneously acquired electroencephalography and functional magnetic resonance imaging (EEG-fMRI) can be strongly affected by motion. Recent work has shown that the quality of fMRI data can be improved by using a Moiré-Phase-Tracker (MPT)-camera system for prospective motion correction. The use of the head position acquired by the MPT-camera-system has also been shown to correct motion-induced voltages, ballistocardiogram (BCG) and gradient artefact residuals separately. In this work we show the concept of an integrated framework based on the general linear model to provide a unified motion informed model of in-MRI artefacts. This model (retrospective EEG motion educated gradient artefact suppression, REEG-MEGAS) is capable of correcting voltage-induced, BCG and gradient artefact residuals of EEG data acquired simultaneously with prospective motion corrected fMRI. In our results, we have verified that applying REEG-MEGAS correction to EEG data acquired during subject motion improves the data quality in terms of motion induced voltages and also GA residuals in comparison to standard Artefact Averaging Subtraction and Retrospective EEG Motion Artefact Suppression. Besides that, we provide preliminary evidence that although adding more regressors to a model may slightly affect the power of physiological signals such as the alpha-rhythm, its application may increase the overall quality of a dataset, particularly when strongly affected by motion. This was verified by analysing the EEG traces, power spectra density and the topographic distribution from two healthy subjects. We also have verified that the correction by REEG-MEGAS improves higher frequency artefact correction by decreasing the power of Gradient Artefact harmonics. Our method showed promising results for decreasing the power of artefacts for frequencies up to 250 Hz. Additionally, REEG-MEGAS is a hybrid framework that can be implemented for real time prospective motion correction of EEG and fMRI data. Among other EEG-fMRI applications, the approach described here may benefit applications such as EEG-fMRI neurofeedback and brain computer interface, which strongly rely on the prospective acquisition and application of motion artefact removal.

Background In osteoporotic vertebral fractures (OVF) involving neurological symptoms and severe kyphosis, vertebral osteotomies are necessary but are associated with a high risk of complications. Methods We performed a retrospective study. In 14 patients (mean age, 69.3 years old) with unstable thoracolumbar fractures associated with severe kyphosis, a posterior instrumentation with polymethylmethacrylate-augmented screws and a modified pedicle subtraction osteotomy (PSO) at the fracture level were performed to stabilize the spine and correct the kyphosis. The underlying principle behind the osteotomy9s technique was to exaggerate the defect caused by the fracture and shorten the spine: (1) completion of a wide laminoforaminotomy, (2) use of successive reamers rotated in the pedicle at a 25° angle in the axial plane to obtain its complete decancellation, (3) insertion of the reamers in a more medial orientation (55°) to collapse the posterior wall, and (4) breakage of the lateral wall. Radiographic and clinical outcomes were analyzed pre- and postoperatively. Complications were reported. Results Functional scores improved after surgery. Oswestry disability index and visual analog scale scores decreased significantly (33 and 4 points, respectively). Patient satisfaction rate reached 93%. Average postoperative regional vertebral kyphosis was decreased to 3.79°. No dural tear or neurological injuries were observed. Blood loss of 920 mL (±350 mL) and two mechanical complications were reported. Conclusions OVF can lead to severe deformities. In osteoporotic bones, the use of sequential reamers can simplify the PSO technique, allowing for the shortening and stabilization of the spine without manipulating the dural sac. The risk of neurological injuries and blood loss is decreased. Level of Evidence 4.

Purpose Tumor size and depth of invasion (DOI) are mandatory assessments for tumor classification in tongue cancer but are often non-assessable on CT due to dental artifacts. This study investigated whether subtraction iodine imaging (SII) would improve tumor delineation and measurability. Materials and methods Fifty-seven consecutive patients with tongue cancer, who underwent scanning with a 320-row area detector CT with contrast administration and were treated with surgical resection, were retrospectively evaluated. CT was reconstructed with single-energy projection-based metallic artifact reduction (sCT). SII was generated by subtracting the pre-contrast volume scans from the post-contrast volume scans using a high-resolution deformable registration algorithm. MRI scans were also evaluated for comparing the ability of measurements. Two radiologists visually graded the tumor delineation using a 5-point scale. Tumor size and DOI were measured wherever possible. The tumor delineation score was compared using the Wilcoxon signed-rank method. Spearman’s correlations between imaging and pathological measurements were calculated. Intraclass correlation coefficients of measurements between readers were estimated. Results The tumor delineation score was greater on sCT-plus-SII than on sCT alone (medians: 3 and 1, respectively; p Conclusions SII improves detectability and measurability of tumor size and DOI in patients with oral tongue squamous cell carcinoma, thus increasing the diagnostic potential. SII may also be beneficial for cases unevaluable on MRI due to artifacts or for patients with contraindications to MRI.

Purpose Dynamic contrast-enhanced MRI (DCE-MRI) registration is a challenging task because of the effect of remarkable intensity changes caused by contrast agent injections. Unrealistic deformation usually occurs by using traditional intensity-based algorithms. To alleviate the effect of contrast agent on registration, we proposed a DCE-MRI registration strategy and investigated the registration performance on the clinical DCE-MRI time series of liver. Method We reconstructed the time-intensity curves of the contrast agent through sparse representation with a predefined dictionary whose columns were the time-intensity curves with high correlations with respect to a preselected contrast agent curve. After reshaping 1D-reconstructed contrast agent time-intensity curves into a 4D contrast agent time series, we aligned the original time series to the reconstructed contrast agent time series through traditional free-form deformation (FFD) registration scheme combined with a residual complexity (RC) similarity and an iterative registration strategy. This study included the DCE-MRI time series of 20 patients with liver cancer. Results Qualitatively, the time-cut images and subtraction images of different registration methods did not obviously differ. Quantitatively, the mean (standard deviation) of temporal intensity smoothness of all the patients achieved 54.910 (18.819), 54.609 (18.859), and 53.391 (19.031) in FFD RC, RDDR, Zhou et al.'s method and the proposed method, respectively. The mean (standard deviation) of changes in the lesion volume were 0.985 (0.041), 0.983 (0.041), 0.981 (0.046), and 0.989 (0.036) in FFD RC, RDDR, Zhou et al.'s method and the proposed method. Conclusion Our proposed method would be an effective registration strategy for DCE-MRI time series, and its performance was comparable with that of three advanced registration methods.

Background: Evaluating the tumor response to neoadjuvant chemotherapy is key to planning further therapy of breast cancer. Our study aimed to evaluate the effectiveness of low-energy and subtraction contrast-enhanced spectral mammography (CESM) images in the detection of complete response (CR) for neoadjuvant chemotherapy (NAC) in breast cancer. Methods: A total of 63 female patients were qualified for our retrospective analysis. Low-energy and subtraction CESM images just before the beginning of NAC and as a follow-up examination 2 weeks before the end of chemotherapy were compared with one another and assessed for compliance with the postoperative histopathological examination (HP). The response to preoperative chemotherapy was evaluated based on the RECIST 1.1 criteria (Response Evaluation Criteria in Solid Tumors). Results: Low-energy images tend to overestimate residual lesions (6.28 mm) and subtraction images tend to underestimate them (2.75 mm). The sensitivity of low-energy images in forecasting CR amounted to 33.33%, while the specificity was 92.86%. In the case of subtraction CESM, the sensitivity amounted to 85.71% and the specificity to 71.42%. Conclusions: CESM is characterized by high sensitivity in the assessment of CR after NAC. The use of only morphological assessment is insufficient. CESM correlates well with the size of residual lesions on histopathological examination but tends to underestimate the dimensions.

Photon subtraction is useful to produce nonclassical states of light addressed to applications in photonic quantum technologies. After a very accelerated development, this technique makes possible obtaining either single photons or optical cats on demand. However, it lacks theoretical formulation enabling precise predictions for the produced fields. Based on the representation generated by the two-mode $SU(2)$ coherent states, we introduce a model of entangled light beams leading to the subtraction of photons in one of the modes, conditioned to the detection of any photon in the other mode. We show that photon subtraction does not produce nonclassical fields from classical fields. It is also derived a compact expression for the output field from which the calculation of conditional probabilities is straightforward for any input state. Examples include the analysis of squeezed-vacuum and odd-squeezed states. We also show that injecting optical cats into a beam splitter gives rise to entangled states in the Bell representation., Comment: 22 pages, 6 figures

Wire ropes (WRs) are widely used in various areas, such as tourist cables, mining, and elevators. Thus, it is very important to detect broken wires (BWs) to prevent safety issues. To guarantee the structural health of WRs, this paper proposes the use of induction thermography (IT) to detect the BWs. An image segmentation algorithm based on scale morphology is proposed to eliminate the background influence of non-uniform heating and visualize the BWs. Further, the area of the BW region, after the image binarization, subtraction, and filtering, is extracted as a feature to quantify the number of BWs. Results show that the proposed methods can effectively visualize and quantify the broken region within 1 BWs.

Background The ability of the patient specific 3D printed neurovascular phantoms to accurately replicate the anatomy and hemodynamics of the chronic neurovascular diseases has been demonstrated by many studies. Acute occurrences, however, may still require further development and investigation and therefore we studied acute ischemic stroke (AIS). The efficacy of endovascular procedures such as mechanical thrombectomy (MT) for the treatment of large vessel occlusion (LVO), can be improved by testing the performance of thrombectomy devices and techniques using patient specific 3D printed neurovascular models. Methods 3D printed phantoms were connected to a flow loop with physiologically relevant flow conditions, including input flow rate and fluid temperature. A simulated blood clot was introduced into the model and placed in the proximal Middle Cerebral Artery (MCA) region. Clot location, composition, length, and arterial angulation were varied and MTs were simulated using stent retrievers. Device placement relative to the clot and the outcome of the thrombectomy were recorded for each situation. Digital subtraction angiograms (DSA) were captured before and after LVO simulation. Recanalization outcome was evaluated using DSA as either ‘no recanalization’ or ‘recanalization’. Forty-two 3DP neurovascular phantom benchtop experiments were performed. Results Clot angulation within the MCA region had the most significant impact on the MT outcome, with a p-value of 0.016. Other factors such as clot location, clot composition, and clot length correlated weakly with the MT outcome. Conclusions This project allowed us to gain knowledge of how such characteristics influence thrombectomy success and can be used in making clinical decisions when planning the procedure and selecting specific thrombectomy tools and approaches.

The achievement of the pathologic complete response (pCR) has been considered a metric for the success of neoadjuvant chemotherapy (NAC) and a powerful surrogate indicator of the risk of recurrence and long-term survival. This study aimed to develop a multimodal deep learning model that combined clinical information and pretreatment MR images for predicting pCR to NAC in patients with breast cancer. The retrospective study cohort consisted of 536 patients with invasive breast cancer who underwent pre-operative NAC. We developed a deep learning model to fuse high-dimensional MR image features and the clinical information for the pretreatment prediction of pCR to NAC in breast cancer. The proposed deep learning model trained on all datasets as clinical information, T1-weighted subtraction images, and T2-weighted images shows better performance with area under the curve (AUC) of 0.888 as compared to the model using only clinical information (AUC = 0.827, P

Adaptive subtraction is a well-established routine technique in seismic data processing that relies on being able to match, in some sense, one dataset to another. It is a necessary part of many processing steps such as de-noising and de-multiple. The same matching methods are also used for advanced imaging steps such as non-stationary estimation of the Hessian as part of image-domain least-squares migration. Predictions of noise are often not as accurate as we would like because there are often shortcomings in the prediction method and because pragmatic acquisition compromises are made. The ubiquity of adaptive subtraction in the seismic processing workflow means there is always motivation to improve its performance. In this work, we propose a deep-learning approach for the adaptive subtraction of predicted multiple models from the input recorded data. It turns out that it is straightforward to use deep-learning networks to perform adaptive subtraction and as a result, benefit from the power of complex non-linear filters. Inspired by the idea of a convolutional autoencoder, we have developed a supervised convolutional autoencoder for adaptive subtraction. We demonstrate the proposed approach on synthetic and field data examples and compare the results using conventional adaptive subtraction methods to illustrate the effectiveness of our approach.

Objective: To systematically evaluate the efficacy and safety of Loquat Qingfei Yin (LQFY) in the treatment of acne. Methods: Using computer retrieval, comprehensive collection of the full text database of Chinese journals till December 2020 (CNKI), Wanfang Data Knowledge Service Platform (Wanfang), Viper Database (VIP), PubMed, Cochrane Library, Medline were included in the LQFY addition or subtraction treatment of acne randomized controlled trial (RCT). Screening of the literatures included in the Note Express 3.2.0. Assessment of the risk of bias in trials using Cochrane collaboration tools, and used Rev Man 5.3 to evaluate the curative effect. Results: 25 RCT, all in Chinese, there were 2257 cases. Of the 1216 cases who were treated, control group was 1041 cases. A random effect model was used for Meta analysis. The results showed that the effective rate of the treatment group was significantly higher than that of the control group, Differences were statistically significant (P=0.94, I2=0%), RR=2.87, CI [2.25,95 per cent 3.67], P

Introduction With intra-arterial digital subtraction angiography (DSA) considered as the gold standard, we compared the diagnostic value of computed tomography angiography (CTA) and computed tomography-digital subtraction angiography (CT-DSA in hemodialysis (HD) patients suspected of having lower limb peripheral artery disease (PAD). Methods In this retrospective study, we enrolled 220 HD patients with suspected PAD. CT-DSA images were obtained by subtracting unenhanced images from enhanced images. The research team calculated the area under the curve (AUC), sensitivity, specificity, positive and negative predictive value (PPV, NPV), and recorded the diagnostic accuracy between the CTA and CT-DSA images using the DSA as gold standard. Visual evaluation of calcifications in the peripheral arteries were also compared between CTA and CT-DSA images. Results At the above-knee level, the CTA AUC [95% confidence interval (CI)] was 0.68 (CI 0.64–0.72), sensitivity and specificity were 60 and 81%, PPV and NPV were 85 and 53%, and accuracy was 67%. Below the knee, these values were 0.66 (CI 0.62–0.70), 71 and 79%, 79 and 47%, and 66%. For CT-DSA, above-knee, the AUC [95% CI] was 0.88 (CI 0.85–0.91), sensitivity and specificity were 84 and 92%, PPV and NPV were 89 and 97%, and accuracy was 93%. Below the knee, these values were 0.95 (CI 0.93–0.97), 95 and 93%, 96 and 83%, and 93%. The scores for the visualization of calcification in the peripheral arteries was significantly higher for CT-DSA than CTA (p Conclusions CT-DSA helps to assess stenotic PAD with high calcification in the lower extremities of HD patients. Implications for practice On CT-DSA images, the severity of vascular calcification can be assessed for HD patients suspected of PAD of the lower extremities.

Rapid detection of distortions formed in the welds of metal has high importance to prevent disasters. Radiography images of the weld have an unlimited number of small defects with diverse shapes. Visual inspection of the weld is a complicated, time-consuming task; and depends on the observers' experience. Many computer-aided detection techniques have emerged as an alternative tool for segmenting the flaws of the weld, but none of them could segment alone all types of weld defects. In this paper, we attempt a possible solution and a novel image-based approach to solve the problem of weld defect detection using a data set of X-ray images. We aim to subtract the background and all horizontal defects and segment the non-horizontal flaws. For that, we apply some morphological operations and wiener filter to enhance the image quality; we use two novel filters to segment the non-horizontal defects; finally, we perform a post-processing operation. Our method depends on two convolution processes between the designed filters and the original image to achieve the segmentation process. We tested our approach on a universally available database of 68 images of the weld. Our method achieved high segmentation accuracy with zero errors. We highlighted the academic advancement of our technique by comparing its performance with other methods. Our efficient approach is effortless, applicable in practical segmentation processes of the defects of the weld. In the future, we will dedicate our work to the segmentation of horizontal defects by altering the shape of the two filters. Our method achieves satisfying accuracy; so, it is promising for weld defect detection. The particular contribution of our technique is that it can segment alone all types of weld defects, contrary to traditional weld defect detection methods. The computing time is optimized compared to other algorithms.

Objective To investigate the feasibility of subtraction coronary computed tomographic (CT) angiography (SubCCTA) to decline calcium artifacts and improve diagnostic accuracy in the presence of coronary calcification and analyze the factors that influence SubCCTA. Methods A total of 294 patients suspected of having coronary artery diseases underwent coronary computed tomographic angiography (CCTA) and SubCCTA. Coronary stenoses were blindly evaluated by two experienced radiologists, which were compared with invasive coronary angiography (ICA). Multiple statistical indexes were adopted to analyze the value of SubCCTA for the diagnosis of calcium stenoses. Results The diagnosable rate of SubCCTA was 67.2% (n=197), and the non-diagnosable rate was 32.8% (n=97). Using SubCCTA, the false positive rate decreased from 56.5% to 17.4%, and the corresponding diagnostic accuracy was increased from 83.6% to 92.9%. Univariate logistic regression analysis showed that height (OR=1.029, 95% CI=1.001-1.058), weight (OR=1.025, 95% CI=1.004-1.046), left ventricular size (OR=1.018, 95% CI=1.007-1.030), cardiothoracic ratio (OR=39.917, 95% CI=1.244-1281.098), the average heart rate (OR=0.866, 95% CI=0.836-0.896) and heart rate range (OR=0.882, 95% CI=0.853-0.912) might be the factors influencing SubCCTA. Conclusion This study suggested that SubCCTA could help improve diagnostic accuracy in the presence of calcium plaques. Moreover, several factors were discovered for the first time to possibly influence SubCCTA, which will be helpful in improving the subtracted image quality.

A computer-generated moire profilometry based on flat image demodulation is proposed. A sinusoidal fringe pattern and its background light are modulated by two-frequency carrier fringes, respectively, to combine a composite grating. While this composite grating is projected onto the measured object, the composite deformed pattern can be captured by CCD camera. So the sinusoidal deformed pattern and its corresponding flat image can be demodulated from the composite deformed pattern. And the AC component of sinusoidal deformed pattern is calculated by the subtraction between the demodulated sinusoidal deformed pattern and the flat image. Compared with normal computer-generated moire profilometry, a more intact AC component can be obtained directly no matter how severe the frequency aliasing condition is. Meanwhile, the three-dimensional (3D) shape of object can be reconstructed only using this composite deformed pattern which shows the application in real-time measurement. Experimental results show the feasibility and validity of the proposed method.

As an important topic in the multimedia and computer vision fields, salient object detection has been researched for years. Recently, state-of-the-art performance has been witnessed with the aid of the fully convolutional networks (FCNs) and the various pyramid-like encoder-decoder frameworks. Starting from a common encoder-decoder architecture, we enhance a residual refinement network with feature purification for better saliency estimation. To this end, we improve the global knowledge streams with intermediate supervisions for global saliency estimation and design a specific feature subtraction module for residual learning, respectively. On the basis of the strengthened network, we also introduce an attribute encoding sub-network (AENet) with a grid aggregation block (GAB) to guide the final saliency predictor to obtain more accurate saliency maps. Furthermore, the network is trained with a novel constraint loss besides the traditional cross-entropy loss to yield the finer results. Extensive experiments on five public benchmarks show our method achieves better or comparable performance compared with previous state-of-the-art methods.

Objective May-Thurner syndrome (MTS) is typically characterized by compression of the left common iliac vein by the overlying right common iliac artery. The present study evaluated the occurrence of atypical imaging features of MTS using three-dimensional computed tomography venography reconstruction (3D-CTV) and analyzed their correlation with clinical features. Methods We analyzed the data from 268 patients with left lower extremity chronic venous disease (CVD) using 3D-CTV at a single institution from January to June 2019. An area stenosis percentage >50% was defined as significant venous compression. Of the 268 patients, 92 had at least one significant iliac and/or vena cava compression confirmed by 3D-CTV. Of the 92 patients, 89 underwent digital subtraction venography via the left common femoral vein, and the outcomes were compared with their 3D-CTV findings. Different types of venous compression were evaluated using 3D-CTV. The relationship among compression type, sex, age, and CVD symptoms was evaluated. Results A total of 106 venous compression sites were found in 92 patients. Atypical compression included inferior vena cava (IVC) compression and partial IVC compression (8.5% and 55.7%, respectively). Multiple compression sites were present in 13 patients (14.1%). The compression sites correlated significantly with clinical symptoms (P = .017) and were related to sex (P = .001). The number of patients with IVC and partial IVC compression but false-negative venography findings was four (33.3%) and six (50%), respectively. Conclusions 3D-CTV facilitates the detection of atypical venous compression in patients with MTS with notable chronic symptoms. Patients with multiple compression sites had more severe clinical symptoms and greater false-negative rates with venography. IVC compression was more likely to occur in female patients with MTS.

Purpose This article describes an innovative technique to confirm needle tip positioning using digital subtraction fluoroscopy and air within a targeted joint. Materials and Methods Digital subtraction fluoroscopy with air was utilized to confirm intra-articular needle tip position in 12 joints over a 14-month period at a single institution. Procedural details were recorded for each joint including: joint location, fluoroscopy time, patient age, patient body mass index, and change in subjective pain rating following the injection. Shoulder and hip phantoms were utilized to compare radiation dose differences between fluoroscopy with digital subtraction technique and fluoroscopy without digital subtraction technique. Results All of the 12 injections were technically successful with air clearly visualized within each targeted joint and subjective pain ratings either did not change or decreased following the injection. Patient age ranged from 51 to 87 years old and body mass index values ranged from 19.2 to 37.1 kg/m2. Fluoroscopy times ranged from 11.1 to 32.9 seconds. There were no complications during or immediately following the injections. The addition of digital subtraction technique increased the skin dose at the shoulder by approximately 2.6 times and at the hip by approximately 2.2 times. Likewise, the cumulative dose at the shoulder increased by approximately 2.7 times and at the hip by 2.0 times. Conclusion Fluoroscopic digital subtraction air arthrography is a valuable option for needle tip confirmation when using air as a contrast agent. This novel combination of established fluoroscopic techniques can be incorporated into most clinical practices.

As the γ-ray energy increases, a reconstructed image becomes noisy and blurred due to the penetration of the γ-ray through the coded mask. Therefore, the thickness of the coded mask was increased for high energy regions, resulting in severely decreased the performance of the detection efficiency due to self-collimation by the mask. In order to overcome the limitation, a modified uniformly redundant array γ-ray imaging system using dual anti-mask method was developed, and its performance was compared and evaluated in high-energy radiation region. In the dual anti-mask method, the two shadow images, including the subtraction of background events, can simultaneously contribute to the reconstructed image. Moreover, the reconstructed images using each shadow image were integrated using a hybrid update maximum likelihood expectation maximization (h-MLEM). Using the quantitative evaluation method, the performance of the dual anti-mask method was compared with the previously developed collimation methods. As the shadow image which was subtracted the background events leads to a higher-quality reconstructed image, the reconstructed image of the dual anti-mask method showed high performance among the three collimation methods. Finally, the quantitative evaluation method proves that the performance of the dual anti-mask method was better than that of the previously reconstruction methods.

Purpose To obtain normal ranges for the inner diameters of the carotid arteries. Methods This retrospective analysis included consecutive patients with disease-free carotid arteries who had undergone 3D-DSA at two hospitals in Nanning, Guangxi, between March 2013 and March 2018. Demographic and clinical characteristics, including Essen Stroke Risk Score (ESRS), were extracted from the medical records. The 3D-DSA data were used to calculate the inner diameters of the carotid arteries. Results The analysis included 1182 patients (837 males) aged 58.81 ± 11.02 years. The inner diameters of the proximal carotid sinus (CS), CS bulge, distal CS, and common carotid artery (CCA) were larger on the right than on the left (P P 65 years than for patients aged ≤ 55 years (P 55 years than for patients aged ≤ 45 years (P P Conclusion This study provides reference values for the internal diameters of normal carotid arteries. Carotid artery diameters varied with side, sex, and age.

Simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is a very promising non‐invasive neuroimaging technique. However, EEG data obtained from the simultaneous EEG–fMRI are strongly influenced by MRI‐related artefacts, namely gradient artefacts (GA) and ballistocardiogram (BCG) artefacts. When compared to the GA correction, the BCG correction is more challenging to remove due to its inherent variabilities and dynamic changes over time. The standard BCG correction (i.e., average artefact subtraction [AAS]), require detecting cardiac pulses from simultaneous electrocardiography (ECG) recording. However, ECG signals are also distorted and will become problematic for detecting reliable cardiac peaks. In this study, we focused on a beamforming spatial filtering technique to attenuate all unwanted source activities outside of the brain. Specifically, we applied the beamforming technique to attenuate the BCG artefact in EEG–fMRI, and also to recover meaningful task‐based neural signals during an attentional network task (ANT) which required participants to identify visual cues and respond accurately. We analysed EEG–fMRI data in 20 healthy participants during the ANT, and compared four different BCG corrections (non‐BCG corrected, AAS BCG corrected, beamforming + AAS BCG corrected, beamforming BCG corrected). We demonstrated that the beamforming approach did not only significantly reduce the BCG artefacts, but also significantly recovered the expected task‐based brain activity when compared to the standard AAS correction. This data‐driven beamforming technique appears promising especially for longer data acquisition of sleep and resting EEG–fMRI. Our findings extend previous work regarding the recovery of meaningful EEG signals by an optimized suppression of MRI‐related artefacts., Our proposed data‐driven beamforming spatial filtering approach outperformed the standard denoising technique in terms of both attenuating the ballistocardiogram (BCG) artefacts and recovering the meaningful task‐based‐induced neural activities in electroencephalography–functional magnetic resonance imaging (EEG–fMRI). This beamforming BCG artefact correction approach neither requires identifying noise and signal components nor relying on simultaneous ECG recording, which makes it promising. Our findings support and extend the previous findings of the beamforming spatial filtering application, and bring new insight into an active area of research in EEG‐fMRI‐related to the extraction of meaningful brain signals and suppression of MRI‐related artefacts.

The chances of acquiring three-dimensional (3D) point clouds have recently increased with the emergence of laser scanners. Hence, 3D monitoring of various objects through the accumulation of “time-series 3D point clouds,” which are point clouds of the same place at different times, is possible. Change detection is a task that is indispensable in 3D monitoring. One of the most common change detection method of 3D point clouds is simple subtraction between two data. However, this method is vulnerable to various errors. Therefore, change detection methods that are robust to errors are required. In this study, we developed robust principal component analysis, which has become popular in the background modelling of video images, to robustly recognize changes in time-series 3D point clouds. We first applied the proposed method to time-series depth images and confirmed its accuracy. We then applied the method to the digital elevation models of Mt. Unzen, which were acquired between 2003 and 2016, to recognize yearly elevation changes. The results show that the proposed method robustly recognizes elevation changes with a properly set parameter.

Several researches attempt to improve the performance in addition and subtraction of fraction by focusing on students’ understanding, such as applying fraction tiles manipulatives and number line in the teaching, or using visual aids such as area model and drawings or virtual diagrams. Similarly, few studies focus on adopting simple procedures that will facilitate students in attempting the topic. Butterfly Method is an approach that not only simplifies the pedagogical approach of learning addition and subtraction of fraction, but also indirectly promotes students’ conceptual understanding in the topic. Yet this approach is not commonly practiced in Brunei. This action research employed quantitative approach involving fourty-one Year 9 IGCSE level students from a government secondary school in Brunei Darussalam. The study aimed to investigate the effect on applying Butterfly Method in the learning of addition and subtraction of fraction through pre-test and post-test. The study revealed a significant improvement in students’ performance through Wilcoxon Signed rank test (Z = 4.2332, p-value < 0.05), with large effect size (r = 0.6611). This is also supported with the improvement of the overall mark distribution of students from pre-test to post-test, with Hake’s normalised gain values indicated majority of the participants achieved high (56.1%), medium (7.32%) and low (2.44%) improvements. Item analysis also indicated overall improvement of correct attempts in questions related to addition and subtraction of fraction, most apparently on fraction problems involving denominators not multiple of each other, improper fractions and mixed numbers. Thus, applying Butterfly Method significantly improved the overall students’ performance in the learning of addition and subtraction of fractions.

During hot fire rocket engine testing, non-contacting measurements are superior to bonded gauges because they are immune to burning, shaking loose, or damage due to the harsh testing conditions. Additionally, when compared to instruments which register at single points, Digital Image Correlation (DIC) has the added benefit in that it collects full-field displacement and strain maps over the duration of the test. However, for certain materials and paints under some circumstances of temperature and camera sensitivity, portions of the speckle pattern which were darker at room temperature may emit more light compared to the initially lighter portions of the pattern, resulting in a high temperature pattern which is inverted in comparison with that at room temperature. To address this inversion, a post-processing method is introduced wherein an inverted image containing only emitted light is subtracted from an image containing both emitted and reflected light, thereby generating an un-inverted image. The artificial high temperature image is subsequently correlated against the room temperature image to obtain full-field strains. The subtraction technique is then validated using optical bandpass filters to prevent significant amounts of emitted light from reaching the camera sensor. The two methods are mapped onto common coordinates and shown to produce comparable results. The subtraction method sufficiently mitigates speckle pattern inversion, but its key drawback is that it only works when there is negligible displacement between the subtracted images (i.e. quasi-static loading). It is therefore preferable to eliminate inversion from reaching the camera in the first place by using optical bandpass filters.

Cross-track interferometry (CTI) for synthetic aperture radars (SARs) is a useful technique that has been widely used to retrieve a digital surface model (DSM). One aim of CTI observations is to measure the heights of objects in a target scene, and a straightforward approach for this purpose is to subtract an external reference of the digital terrain model (DTM) from the CTI DSM. On the other hand, the refinement of parameters for CTI, namely interferometric SAR (InSAR) parameters, using an external reference is often required before subtraction. To avoid undesired degradation caused by potential differences in the terrain height between the references used for subtraction and refinement, it is preferable to use a single DTM as a common reference. However, InSAR parameters cannot be refined correctly if a DTM is used as an external source for GCPs without careful considerations since a CTI DSM contains objects unlike a DTM. In this context, we propose a novel method that refines InSAR parameters based on a DTM. The features of the proposed method are that automatically extracted footprints of vertical structures are selected as ground control point (GCP) candidates and that GCPs expected to lie at the terrain level are iteratively selected by fitting the histogram of the height difference with one or two normal distributions. This enables us to refine InSAR parameters with a single CTI DSM dataset and an external DTM without any interactive operations in the process. An experiment based on a real CTI dataset for a complex scene and a laser DTM demonstrates the promising performance of the proposed method. The median and interquartile range of the height error in terrain areas for the test scene are −0.18 m and 1.81 m, respectively, which are acceptable for various applications. The degrees of improvement resulting from the use of two novel ideas in the test scene are found to be comparable. The proposed method is predicted to be effective for developed areas such as urban and residential areas owing to its inherent limitations.

Background Digits-in-noise (DIN) tests have become popular for hearing screening over the past 15 years. Several recent studies have highlighted the potential utility of DIN as a school-aged hearing test. However, age may influence test performance in children due to maturation. In addition, a new antiphasic stimulus paradigm has been introduced, allowing binaural intelligibility level difference (BILD) to be measured by using a combination of conventional diotic and antiphasic DIN. Purpose This study determined age-specific normative data for diotic and antiphasic DIN, and a derived measure, BILD, in children. A secondary aim evaluated the validity of DIN as a smartphone self-test in a subgroup of young children. Research Design A cross-sectional, quantitative design was used. Participants with confirmed normal audiometric hearing were tested with a diotic and antiphasic DIN. During the test, arrangements of three spoken digits were presented in noise via headphones at varying signal-to-noise ratio (SNR). Researchers entered each three-digit spoken sequence repeated by the participant on a smartphone keypad. Study Sample Overall, 621 (428 male and 193 female) normal hearing children (bilateral pure tone threshold of ≤ 20 dB hearing level at 1, 2, and 4 kHz) ranging between the ages of 6 and 13 years were recruited. A subgroup of 7-year-olds (n = 30), complying with the same selection criteria, was selected to determine the validity of self-testing. Data Collection and Analysis DIN testing was completed via headphones coupled to a smartphone. Diotic and antiphasic DIN speech recognition thresholds (SRTs) were analyzed and compared for each age group. BILD was calculated through subtraction of antiphasic from diotic SRTs. Multiple linear regressions were run to determine the effect of age on SRT and BILD. In addition, piecewise linear regressions were fit across different age groups. Wilcoxon signed-rank tests were used to determine differences between self- and facilitated tests. Results Age was a significant predictor, of both diotic and antiphasic DIN SRTs (p 0.05). Conclusions Increasing age was significantly associated with improved SRT and BILD using diotic and antiphasic DINs. DIN could be used as a smartphone self-test in young children from 7 years of age with appropriate quality control measures to avoid potential false positives.

The subject of Boolean subtraction and division dates back for over a century to the work of George Boole. Nevertheless, this subject is unfamiliar to us because it has been banished from Boolean algebra. In fact, some authors claim that there is no such thing as Boolean subtraction and division. The purpose of this work, however, is to present with clarity the subject of logical subtraction and division and its practical application in the design of digital circuits.

OBJECTIVE The aim of the study was to determine the accuracy of postvoid residual (PVR) by subtraction as compared with objective measurement by bladder scan or catheterization. METHODS This is a secondary analysis of postoperative patients who underwent avoiding trial by retrograde bladder instillation. Fill volume, spontaneous voided volume, and PVR were objectively measured; PVR was also calculated. Pearson correlation compared PVR by subtraction versus objective measurement. We then defined postoperative urinary retention (POUR) at 3 different PVR values (100 mL, 150 mL, and 200 mL) to compare the sensitivity, specificity, and positive and negative predictive values of subtraction for detecting urinary retention at these 3 thresholds. RESULTS Data were available for 155 patients after urogynecologic surgery. Median PVR by objective measurement was 46 mL (interquartile range = 11-146 mL). Median calculated PVR by subtraction was 10 mL (interquartile range = 0-100 mL). Objective measure and subtraction PVR values were strongly correlated (Pearson coefficient = 0.78, P < 0.001). Using a threshold of 200 mL to define POUR resulted in the highest negative predictive value and the lowest absolute number of both false negatives and false positives. Even using this threshold, 11 (48%) of 23 women with POUR by measurement were misclassified as not having POUR when ascertained by subtraction. CONCLUSIONS Although subtraction PVR correlates well with objective PVR measurement, almost half of women with a PVR volume of greater than 200 mL by objective measurement are miscategorized as voiding normally by subtraction PVR. Based on these findings, reliance on objective PVR measurement in postoperative patients is preferable to subtraction PVR.

With the ability to generate different spiking patterns, Izhikevich model has well been considered a computationally efficient and biologically plausible neuron model for applications such as brain dynamic behavior study. This brief presents a low-cost, high-throughput digital hardware design for Izhikevich neuron model. The proposed design requires only addition, subtraction and logic shifts operations to achieve the low hardware cost. The dynamic behaviors of both the proposed neuron model and the original Izhikevich model were analyzed using the phase portraits. The FPGA implementation results demonstrated that the proposed design can reproduce different spiking patterns with very high throughput. Compared to existing designs, the proposed design achieves the lowest slices and LUTs utilization, which are 73% and 11% lower than the latest design (HOMIN), respectively.

OBJECTIVE. The purpose of this article was to evaluate MRI features of uterine leiomyomas that predict volumetric response after uterine artery embolization (UAE). MATERIALS AND METHODS. This retrospective study included 75 patients with 212 uterine leiomyomas who were successfully treated between August 2013 and December 2018. To predict uterine volumetric response, age, number of lesions, and baseline uterine volume were assessed. To predict leiomyoma volumetric response, a multivariate regression analysis was performed to evaluate six predictive factors: location, baseline leiomyoma volume, signal intensity on T1-weighted and T2-weighted MRI, heterogeneity of signal intensity on T2-weighted MRI, and vascularity on subtraction imaging (SI). A five-variable predictive ROC model was developed to evaluate the diagnostic accuracy of the signal intensity ratio on T2-weighted MRI, enhancement ratio, heterogeneity ratio on T2-weighted MRI, location, and baseline leiomyoma volume in predicting at least 40% leiomyoma volumetric response. RESULTS. Age, number of leiomyomas, and baseline uterine volume were not predictive of uterine volumetric response. A submucosal location was the best predictive factor of leiomyoma volumetric response, and it showed 32.2% more leiomyoma volumetric response compared with a nonsubmucosal location (p < .001). Hyperintensity on T2-weighted MRI was the second best predictive factor of leiomyoma volumetric response, and it showed 16.9% more volumetric response compared with hypointense leiomyomas (p = .013). A small baseline leiomyoma volume (< 58 cm3) was associated with 10.2% more leiomyoma volumetric response compared with larger leiomyomas (p = .01). Leiomyomas that were hyperintense on SI showed 7.9% more leiomyoma volumetric response compared with those that were hypointense (p = .014). The five-variable ROC model showed high diagnostic accuracy with an AUC of 0.85, sensitivity of 82%, and specificity of 71%. CONCLUSION. A submucosal location, hyperintensity on T2-weighted MRI, small baseline leiomyoma volume (< 58 cm3), and hyperintense leiomyoma on subtraction imaging are the main independent favorable predictors of leiomyoma volumetric response after UAE. An accurate predictive ROC model was developed that may help in selecting patients suitable for UAE. Quantitative assessment of heterogeneity on T2-weighted MRI showed promising results as a predictor of volumetric response, and further research in this area using texture analysis and radiomics is suggested.

Study Design: A retrospective study. Objective: To investigate the effect of pedicle subtraction osteotomy (PSO) level on the surgical outcomes in ankylosing spondylitis-related thoracolumbar kyphosis with the same curve pattern. Methods: ankylosing spondylitis (AS) patients with thoracolumbar kyphosis, who underwent 1-level lumbar PSO between March 2006 and June 2017, were retrospectively reviewed. Criteria for curve-matched thoracolumbar kyphosis were: (1) have same level of preoperative apex (pre-apex); (2) have similar global kyphosis (GK, the angle between the superior/inferior endplate of the maximally tilted upper and lower end vertebra) (the difference of GK less than 15˚). The radiographic parameters measured were sagittal vertical axis (SVA, the horizontal distance between the C7 plumb line and the posterosuperior corner of the S1), GK, thoracic kyphosis (TK, the angle between the T5 superior endplate and the T12 inferior endplate), lumbar lordosis (LL, the angle between the L1 and S1 superior endplate), sacral slope (SS, the angle between the sacral endplate and the horizontal line), pelvic tilt (PT, the angle between the vertical and the line joining the midpoint of the sacral plate and hip axis), and pelvic incidence (PI, the angle between the line vertical to the superior margin of S1 and the line connecting the sacral plate midpoint with the hip joint axis). All of these parameters and health-related quality of life (HRQoL, evaluated by preoperative and the last follow-up questionnaires including ODI and VAS) scores were collected before surgery and at the last follow-up. According to their osteotomy level, patients were devided into 2 sub-groups (L1 group and L2 group), and differences of these mentioned parameters between 2 groups were compared. Results: 26 curve-matched patients were recruited with a mean follow-up of 37.2 months. All patients improved significantly after surgery in HRQoL scores (VAS 1.6 vs 5.4, P < 0.001; ODI 11.9 vs 26.4, P < 0.001). Except for TK and PI, those radiographic parameters were also observed to be significantly changed after surgery. Compared to L2 group, PSO at L1 may have larger correction of TK (ΔTK -6.8 vs -0.3°, P = 0.164), PI (ΔPI -7.4 vs -0.7°, P = 0.364) and smaller correction of SVA (ΔSVA -105.3 vs -128.5 mm, P = 0.096), LL (ΔLL -31.1 vs -43.0°, P = 0.307) and SS (ΔSS 6.9 vs 12.2°, P = 0.279) but had no statistical significance. Conclusion: The results of this investigation showed that in AS-related thoracolumbar kyphosis patients with the same curve pattern, the different levels of osteotomy had little effect on the improvement of surgical outcomes. However, osteotomy at L2 is more likely to obtain a larger correction of SVA compared to osteotomy at L1.

Image acquisition through a single-sensor camera captures only a fraction of the image data renowned as the raw image. It uses the colour filter array to acquire only a single colour channel in each pixel location. The reconstruction of the so called raw image into a full colour image is known as demosaicking or interpolation. Demosaicking is a significant process in the imaging pipeline. It implicates the reconstruction of the missing two colour channels from an incomplete image obtained from a single-sensor digital camera. This paper proposes a new approach of combining polyscale gradients algorithm and residual demosaicking. The first phase utilizes the gradients at different scales and residual demosaicking (RD) involves subtraction of the pragmatic and the provisional pixel values in the residual province takes place in the second phase. The experimental results show that the proposed demosaicking algorithm outperforms the conventional demosaicking algorithms for the Kodak and McMaster (McM) dataset.

Background Virtual unenhanced (VUE) images obtained by using a dual-energy CT (DECT) multimaterial decomposition algorithm hold promise for diagnostic use in the abdomen in lieu of true unenhanced (TUE) images. Purpose To assess VUE images obtained from a DECT multimaterial decomposition algorithm in patients undergoing renal mass and urinary stone evaluation. Materials and Methods In this retrospective Health Insurance Portability and Accountability Act-compliant study, DECT was performed in patients undergoing evaluation for renal mass or urinary stone. VUE images were compared quantitatively to TUE images and qualitatively assessed by four independent radiologists. Differences in attenuation between VUE and TUE images were summarized by using 95% limits of agreement. Diagnostic performance in urinary stone detection was summarized by using area under the receiver operating characteristic curve, sensitivity, and specificity. Results A total of 221 patients (mean age ± standard deviation, 61 years ± 14; 129 men) with 273 renal masses were evaluated. Differences in renal mass attenuation between VUE and TUE images were within 3 HU for both enhancing masses (95% limits of agreement, -3.1 HU to 2.7 HU) and nonenhancing cysts (95% limits of agreement, -2.9 HU to 2.5 HU). Renal mass classification as enhancing mass versus nonenhancing cyst did not change (reclassification rate of enhancing masses, 0% [0 of 78]; 95% CI: 0, 5; reclassification rate of nonenhancing cysts, 0% [0 of 193]; 95% CI: 0, 2) with use of VUE in lieu of TUE images. Among 166 urinary stones evaluated, diagnostic performance of VUE images for stone detection was lower compared with that of TUE images (area under the receiver operating characteristic curve, 0.79 [95% CI: 0.73, 0.84] vs 0.93 [95% CI: 0.91, 0.95]; P < .001) due to reduced sensitivity of VUE for detection of stones 3 mm in diameter or less compared with those greater than 3 mm (sensitivity, 23% [25 of 108; 95% CI: 12, 40] vs 88% [126 of 144; 95% CI: 77, 94]; P < .001). Conclusion Compared with true unenhanced images, virtual unenhanced (VUE) images were unlikely to change renal mass classification as enhancing mass versus nonenhancing cyst. Diagnostic performance of VUE images remained suboptimal for urinary stone detection due to subtraction of stones 3 mm or less in diameter. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Sosna in this issue.