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Metal artifacts notoriously pose significant challenge in computed tomography (CT), leading to inaccuracies in image formation and interpretation. Artifact reduction tools have been designed to improve cone beam computed tomography (CBCT) image quality by reducing artifacts caused by certain high-density materials. Metal artifact reduction (MAR) tools are specific algorithms that are applied during image reconstruction to minimize or eliminate artifacts degrading CBCT images. The purpose of the study is to evaluate the effect of a MAR algorithm on image quality in CBCT performed for evaluating patients before transarterial radioembolization (TARE). We retrospectively included 40 consecutive patients (aged 65 ± 13 years; 23 males) who underwent 45 CBCT examinations (Allura FD 20, XperCT Roll protocol, Philips Healthcare, Best, The Netherlands) in the setting of evaluation for TARE between January 2017 and December 2018. Artifacts caused by coils, catheters, and surgical clips were scored subjectively by four readers on a 5-point scale (1 = artifacts affecting diagnostic information to 5 = no artifacts) using a side-by-side display of uncorrected and MAR-corrected images. In addition, readers scored tumor visibility and vessel discrimination. MAR-corrected images were assigned higher scores, indicating better image quality. The differences between the measurements with and without MAR were most impressive for coils with a mean improvement of 1.6 points (95%CI [1.5 1.8]) on the 5-point likert scale, followed by catheters 1.4 points (95%CI [1.3 1.5]) and clips 0.7 points (95%CI [0.3 1.1]). Improvements for other artifact sources were consistent but relatively small (below 0.25 points on average). Interrater agreement was good to perfect (Kendall's W coefficient = 0.68–0.95) and was higher for MAR-corrected images, indicating that MAR improves diagnostic accuracy. A metal artifact reduction algorithm can improve diagnostic and interventional accuracy of cone beam CT in patients undergoing radioembolization by reducing artifacts caused by diagnostic catheters and coils, lowering interference of metal artifacts with adjacent major structures, and improving tumor visibility. [ABSTRACT FROM AUTHOR]

A new generation cone‐beam computed tomography (CBCT) system with new hardware design and advanced image reconstruction algorithms is available for radiation treatment simulation or adaptive radiotherapy (HyperSight CBCT imaging solution, Varian Medical Systems‐a Siemens Healthineers company). This study assesses the CBCT image quality metrics using the criteria routinely used for diagnostic CT scanner accreditation as a first step towards the future use of HyperSight CBCT images for treatment planning and target/organ delineations. Image performance was evaluated using American College of Radiology (ACR) Program accreditation phantom tests for diagnostic computed tomography systems (CTs) and compared HyperSight images with a standard treatment planning diagnostic CT scanner (Siemens SOMATOM Edge) and with existing CBCT systems (Varian TrueBeam version 2.7 and Varian Halcyon version 2.0). Image quality performance for all Varian HyperSight CBCT vendor‐provided imaging protocols were assessed using ACR head and body ring CT phantoms, then compared to existing imaging modalities. Image quality analysis metrics included contrast‐to‐noise (CNR), spatial resolution, Hounsfield number (HU) accuracy, image scaling, and uniformity. All image quality assessments were made following the recommendations and passing criteria provided by the ACR. The Varian HyperSight CBCT imaging system demonstrated excellent image quality, with the majority of vendor‐provided imaging protocols capable of passing all ACR CT accreditation standards. Nearly all (8/11) vendor‐provided protocols passed ACR criteria using the ACR head phantom, with the Abdomen Large, Pelvis Large, and H&N vendor‐provided protocols produced HU uniformity values slightly exceeding passing criteria but remained within the allowable minor deviation levels (5–7 HU maximum differences). Compared to other existing CT and CBCT imaging modalities, both HyperSight Head and Pelvis imaging protocols matched the performance of the SOMATOM CT scanner, and both the HyperSight and SOMATOM CT substantially surpassed the performance of the Halcyon 2.0 and TrueBeam version 2.7 systems. Varian HyperSight CBCT imaging system could pass almost all tests for all vendor‐provided protocols using ACR accreditation criteria, with image quality similar to those produced by diagnostic CT scanners and significantly better than existing linac‐based CBCT imaging systems. [ABSTRACT FROM AUTHOR]

Purpose: It is challenging to achieve appropriate target coverage of the prostate with Image Guided Radiation Therapy (IGRT) while simultaneously constraining rectal doses within planned values when there is significant variability in rectal filling and shape. We investigated if rectum planning goals can be fulfilled using rigid CBCT‐based on‐board alignment to account for interfraction rectal deformations. Methods: Delivered rectal doses corresponding to prostate alignment ("PR") and anterior rectum alignment ("AR") for 239 daily treatments from 13 patients are reported. Rectal doses were estimated by rigidly mapping the planned dose on the daily CT derived from the daily CBCT according to respective alignment shifts. Rectum V95% (rV95%) was used for analyses. Results: Compared to "PR", "AR" alignment increased rV95% for an average of 34.4% across all patients. rV95% (cc) averaged over all fractions was significant from planning values for 10/13 patients for "PR" and for 9/13 for "AR". 3/13 patients had reproducible anatomy. Of patients with non‐reproducible anatomy, three had dosimetrically more favorable, while seven had less favorable anatomies. Most shift differences (82.3%) between the "PR" and "AR" alignments larger than 2 mm resulted in rV95% changes larger than 2 cc. Most shift differences (82.2%) of 2 mm or less between the "PR" and "AR" alignments resulted in rV95% changes less than 2 cc. The average percentage of fractions among patients in which anterior or posterior shifts for "AR" and "PR" alignment was larger than the PTV margins was 9.1% (0.0%–37.5%) and 1.3% (0%–10%). Conclusion: Rectal deformation and subsequent inconsistent interfraction separation between prostate and rectal wall translate into anatomical changes that cannot always be mitigated with rigid alignment. If systematic differences exist due to a non‐reproducible planning anatomy, attempts to restore the planned rectal doses through anterior rectum alignment produce rather small improvements and may result in unacceptable target underdosage. [ABSTRACT FROM AUTHOR]

Established kilovoltage cone‐beam computed tomography (kV‐CBCT) image quality assurance (QA) guidelines often rely on recommendations provided by the American Association of Physicists in Medicine (AAPM) task group (TG) reports with metrics that use visual analysis. This can result in measurement variations by different users, especially in visually subjective analyzes such as low contrast resolution. Consequently, there is a growing interest in more automated means of image QA analysis that can offer increased consistency, accuracy, and convenience. This work compares visual QA to semi‐automated software QA analysis to establish the performance and viability of a semi‐automated method. In this study, a commercial product (RIT Radia. Radiological Imaging Technology, Colorado Springs, CO) was used to evaluate 68 months of kV‐CBCT images of a Catphan® 504 phantom obtained from a Varian TrueBeam® linear accelerator. Six key metrics were examined: high contrast resolution, low contrast resolution, Hounsfield unit constancy, uniformity and noise, and spatial linearity. The results of this method were then compared to those recorded visually using Bland‐Altman, and/or paired sample t‐test. Comparison of all modules showed a non‐random, statistically significant difference between visual and semi‐automated methods except for LDPE and Teflon in the Hounsfield unit constancy analysis, which falls outside the paired sample t‐test's 5% significance level. A small high contrast resolution bias indicates the two analysis methods are largely equivalent, while a large low contrast resolution bias indicates greater semi‐automated target detection. Wide limits of agreement in the uniformity module suggests variability due to multiple visual observers. Spatial linearity results measured differences of less than 0.17%. Semi‐automated QA analysis offered greater stability over visual analysis. Additionally, semi‐automated QA results satisfied or exceeded visual QA passing criteria and allowed for fast and consistent image quality analysis. [ABSTRACT FROM AUTHOR]

The feasibility of full-scan, offset-detector geometry cone-beam CT has been demonstrated for several clinical applications. For full-scan acquisition with offset-detector geometry, data redundancy from complementary views can be exploited during image reconstruction. Envisioning an upright breast CT system, we propose to acquire short-scan data in conjunction with offset-detector geometry. To tackle the resulting incomplete data, we have developed a self-supervised attenuation field network (AFN). AFN leverages the inherent redundancy of cone-beam CT data through coordinate-based representation and known imaging physics. A trained AFN can query attenuation coefficients using their respective coordinates or synthesize projection data including the missing projections. The AFN was evaluated using clinical cone-beam breast CT datasets (n = 50). While conventional analytical and iterative reconstruction methods failed to reconstruct the incomplete data, AFN reconstruction was not statistically different from the reference reconstruction obtained using full-scan, full-detector data in terms of image noise, image contrast, and the full width at half maximum of calcifications. This study indicates the feasibility of a simultaneous short-scan and offset-detector geometry for dedicated breast CT imaging. The proposed AFN technique can potentially be expanded to other cone-beam CT applications. [ABSTRACT FROM AUTHOR]

The process of creating virtual models of dentomaxillofacial structures through three-dimensional segmentation is a crucial component of most digital dental workflows. This process is typically performed using manual or semi-automated approaches, which can be time-consuming and subject to observer bias. The aim of this study was to train and assess the performance of a convolutional neural network (CNN)-based online cloud platform for automated segmentation of maxillary impacted canine on CBCT image. A total of 100 CBCT images with maxillary canine impactions were randomly allocated into two groups: a training set (n = 50) and a testing set (n = 50). The training set was used to train the CNN model and the testing set was employed to evaluate the model performance. Both tasks were performed on an online cloud-based platform, 'Virtual patient creator' (Relu, Leuven, Belgium). The performance was assessed using voxel- and surface-based comparison between automated and semi-automated ground truth segmentations. In addition, the time required for segmentation was also calculated. The automated tool showed high performance for segmenting impacted canines with a dice similarity coefficient of 0.99 ± 0.02. Moreover, it was 24 times faster than semi-automated approach. The proposed CNN model achieved fast, consistent, and precise segmentation of maxillary impacted canines. [ABSTRACT FROM AUTHOR]

Computed tomography (CT) has been developed as a nondestructive technique for observing minute internal images in samples. It has been difficult to obtain photorealistic (clean or clear) CT images due to various unwanted artifacts generated during the CT scanning process, along with the limitations of back-projection algorithms. Recently, an iterative optimization algorithm has been developed that uses an entire sinogram to reduce errors caused by artifacts. In this paper, we introduce a new quantum algorithm for reconstructing CT images. This algorithm can be used with any type of light source as long as the projection is defined. Assuming an experimental sinogram produced by a Radon transform, to find the CT image of this sinogram, we express the CT image as a combination of qubits. After acquiring the Radon transform of the undetermined CT image, we combine the actual sinogram and the optimized qubits. The global energy optimization value used here can determine the value of qubits through a gate model quantum computer or quantum annealer. In particular, the new algorithm can also be used for cone-beam CT image reconstruction and for medical imaging. [ABSTRACT FROM AUTHOR]

Introduction: In the Library‐of‐Plans (LoP) approach, correct plan selection is essential for delivering radiotherapy treatment accurately. However, poor image quality of the cone‐beam computed tomography (CBCT) may introduce inter‐observer variability and thereby hamper accurate plan selection. In this study, we investigated whether new techniques to improve the CBCT image quality and improve consistency in plan selection, affects the accuracy of LoP selection in cervical cancer patients. Materials and methods: CBCT images of 12 patients were used to investigate the inter‐observer variability of plan selection based on different CBCT image types. Six observers were asked to individually select a plan based on clinical X‐ray Volumetric Imaging (XVI) CBCT, iterative reconstructed CBCT (iCBCT) and synthetic CTs (sCT). Selections were performed before and after a consensus meeting with the entire group, in which guidelines were created. A scoring by all observers on the image quality and plan selection procedure was also included. For plan selection, Fleiss' kappa (κ) statistical test was used to determine the inter‐observer variability within one image type. Results: The agreement between observers was significantly higher on sCT compared to CBCT. The consensus meeting improved the duration and inter‐observer variability. In this manuscript, the guidelines attributed the overall results in the plan selection. Before the meeting, the gold standard was selected in 76% of the cases on XVI CBCT, 74% on iCBCT, and 76% on sCT. After the meeting, the gold standard was selected in 83% of the cases on XVI CBCT, 81% on iCBCT, and 90% on sCT. Conclusion: The use of sCTs can increase the agreement of plan selection among observers and the gold standard was indicated to be selected more often. It is important that clear guidelines for plan selection are implemented in order to benefit from the increased image quality, accurate selection, and decrease inter‐observer variability. [ABSTRACT FROM AUTHOR]

In this study, we aimed to enhance the contouring accuracy of cardiac pacemakers by improving their visualization using deep learning models to predict MV CBCT images based on kV CT or CBCT images. Ten pacemakers and four thorax phantoms were included, creating a total of 35 combinations. Each combination was imaged on a Varian Halcyon (kV/MV CBCT images) and Siemens SOMATOM CT scanner (kV CT images). Two generative adversarial network (GAN)-based models, cycleGAN and conditional GAN (cGAN), were trained to generate synthetic MV (sMV) CBCT images from kV CT/CBCT images using twenty-eight datasets (80%). The pacemakers in the sMV CBCT images and original MV CBCT images were manually delineated and reviewed by three users. The Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and mean surface distance (MSD) were used to compare contour accuracy. Visual inspection showed the improved visualization of pacemakers on sMV CBCT images compared to original kV CT/CBCT images. Moreover, cGAN demonstrated superior performance in enhancing pacemaker visualization compared to cycleGAN. The mean DSC, HD95, and MSD for contours on sMV CBCT images generated from kV CT/CBCT images were 0.91 ± 0.02/0.92 ± 0.01, 1.38 ± 0.31 mm/1.18 ± 0.20 mm, and 0.42 ± 0.07 mm/0.36 ± 0.06 mm using the cGAN model. Deep learning-based methods, specifically cycleGAN and cGAN, can effectively enhance the visualization of pacemakers in thorax kV CT/CBCT images, therefore improving the contouring precision of these devices. [ABSTRACT FROM AUTHOR]

In order to meet the heavy backprojection calculation of the backprojection filtration (BPF) algorithm in circular cone-beam computed tomography (CT), a fast backprojection method is developed, which uses the integral operator of the fixed scanning angle integral interval. The proposed method combines with Hilbert filtration and the filter of the Blackman window, and then, the fast BPF (F-BPF) algorithm is obtained. The experimental results of simulation data and real data demonstrate that the proposed algorithm is fast enough for high-quality reconstructed images only with half-circle projection data. [ABSTRACT FROM AUTHOR]

There has been an increase in the use of interventional neuroradiology procedures because of their non-invasiveness compared to surgeries and the improved image quality of fluoroscopy, digital subtraction angiography, and rotational angiography. Although cone-beam computed tomography (CBCT) images are inferior to multi-detector CT images in terms of low-contrast detectability and lower radiation doses, CBCT scans are frequently performed because of their accessibility. This study aimed to evaluate the image quality and radiation dose of two different high-resolution CBCTs (HR CBCT): conventional (C-HR CBCT) and wide-field HR CBCT (W-HR CBCT). The modulation transfer function (MTF), noise power spectrum (NPS), and contrast-to-noise ratio (CNR) were used to evaluate the image quality. On comparing the MTF of C-HR CBCT with a 256 × 256 matrix and that of W-HR CBCT with a 384 × 384 matrix, the MTF of W-HR CBCT with the 384 × 384 matrix was larger. A comparison of the NPS and CNR of C-HR CBCT with a 256 × 256 matrix and W-HR CBCT with a 384 × 384 matrix showed that both values were comparable. The reference air kerma values were equal for C-HR CBCT and W-HR CBCT; however, the value of the kerma area product was 1.44 times higher for W-HR CBCT compared to C-HR CBCT. The W-HR CBCT allowed for improved spatial resolution while maintaining the image noise and low-contrast detectability by changing the number of image matrices from 256 × 256 to 384 × 384. Our study revealed the image characteristics and radiation dose of W-HR CBCT. Given its advantages of low-contrast detectability and wide-area imaging with high spatial resolution, W-HR CBCT may be useful in interventional neuroradiology for acute ischemic stroke. [ABSTRACT FROM AUTHOR]

Background: For the reconstruction of Cone-Beam CT volumes, the exact position of each projection is needed; however, in some situations, this information is missing. Purpose: The development of a self-calibration algorithm for arbitrary CBCT trajectories that does not need initial positions. Methods: Projections are simulated in a spherical grid around the center of rotation. Through using feature detection and matching, an acquired projection is compared to each simulated image in this grid. The position with the most matched features was used as a starting point for a fine calibration with a state-of-the-art algorithm. Evaluation: This approach is compared with the calibration of nearly correct starting positions when using FORCASTER and CMA-ES minimization with a normalized gradient information (NGI) objective function. The comparison metrics were the normalized root mean squared error, structural similarity index, and the dice coefficient, which were evaluated on the segmentation of a metal object. Results: The parameter estimation for a regular Cone-Beam CT with a 496 projection took 1:26 h with the following metric values: NRMSE = 0.0669; SSIM = 0.992; NGI = 0.75; and Dice = 0.96. FORCASTER with parameter estimation took 3:28 h with the following metrics: NRMSE = 0.0190; SSIM = 0.999; NGI = 0.92; and Dice = 0.99. CMA-ES with parameter estimation took 5:39 h with the following metrics: NRMSE = 0.0037; SSIM = 1.0; NGI = 0.98; and Dice = 1.0. Conclusions: The proposed algorithm can determine the parameters of the projection orientations for arbitrary trajectories with enough accuracy to reconstruct a 3D volume with low errors. [ABSTRACT FROM AUTHOR]

Aim and Objectives: The purpose of this study was to use cone bar CT to investigate the root trench morphology of two-hundred mesiobuccal permanent first molars in the maxilla. Materials and Methods: The distobuccal and palatal roots were removed at the furcation in 250 maxillary first molars. The mesiobuccal roots were then imaged using cone beam computed tomography on all specimens. The specimens were analyzed and compared to one another." This study looked into the following factors. How Many Canals There Are and What Shape Those Canals Take Errors such as lateral canals, apical delta, calcified segments, and others. Result: Vertucci's trench configuration, kinds I, II, III, IV, V, and VII, were seen in 30%, 20%, 5%, 6%, 7%, and 2.5% of the teeth, respectively. Calcified sections were found in the coronal third of the MB1 trench for eight of the samples, and in the central third for two of the samples. The MB1 trench did not have any calcifications at its very end. The coronal 33 percent of the MB2 trench was calcified in eight samples, but no calcifications were seen in the middle or upper thirds. Conclusion: Noninvasively and with little radiation, a cone beam CT scan can help you learn about your root canal setup. [ABSTRACT FROM AUTHOR]

The pulp–tooth area ratio (PTR) from radiographic dental archives is considered useful for age estimation in the forensic field. Since there have been no studies conducted in the Saudi Arabian population using the PTR method, this study aimed to assess the relationship between the pulp–tooth area ratio of maxillary canines and central incisors and chronological age among Saudi Arabian adults using CBCT and to compare the selected teeth's predictive power. For this, 100 CBCT scans of 62 male and 38 female patients aged between 20 and 60 years were assessed using OnDemand 3D DentalTM software (Cybermed Co., Tustin, CA, USA) in the axial and sagittal section of each tooth. The mean age estimated using the PTR of the maxillary incisors (39.98 years) was higher than the canines' (37.9 years). A negative correlation coefficient 'r' value was seen between PTR and age. The strongest inverse correlation was noted between age and incisor axial view (0.47) (p < 0.05), Maxillary central incisors had higher R2 in both genders (males: PTRS-0.18, PTRA-0.17; females: PTRS-0.19, PTRA-0.35) than canines. We conclude a weak correlation between the pulp–tooth ratio and chronological age estimation. CBCT pulp–tooth ratios of axial and sagittal sections of incisors were inconclusive in estimating the age of Saudi Arabian individuals owing to their low coefficient of estimation. Among the tooth types studied, maxillary incisors were better predictors than canines. [ABSTRACT FROM AUTHOR]

Background and objective: Cone‐beam computed tomography (CBCT) has become a more and more active cutting‐edge topic in the international computed tomography (CT) research due to its advantages of fast scanning speed, high ray utilization rate and high precision. However, scatter artifacts affect the imaging performance of CBCT, which hinders its application seriously. Therefore, our study aimed to propose a novel algorithm for scatter artifacts suppression in thorax CBCT based on a feature fusion residual network (FFRN), where the contextual loss was introduced to adapt the unpaired datasets better. Methods: In the method we proposed, a FFRN with contextual loss was used to reduce CBCT artifacts in the region of chest. Unlike L1 or L2 loss, the contextual loss function makes input images which are not aligned strictly in space available, so we performed it on our unpaired datasets. The algorithm aims to reduce artifacts via studying the mapping between CBCT and CT images, where the CBCT images were set as the beginning while planning CT images as the end. Results: The proposed method effectively removes artifacts in thorax CBCT, including shadow artifacts and cup artifacts which can be collectively referred to as uneven grayscale artifacts, in the CBCT image, and perform well in preserving details and maintaining the original shape. In addition, the average PSNR number of our proposed method achieved 27.7, which was higher than the methods this paper referred which indicated the significance of our method. Conclusions: What is revealed by the results is that our method provides a highly effective, rapid, and robust solution for the removal of scatter artifacts in thorax CBCT images. Moreover, as is shown in Table 1, our method has demonstrated better artifact reduction capability than other methods. [ABSTRACT FROM AUTHOR]

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The root canal morphology undergoes aging-related changes, and relevant quantitative analyses have not yet been reported. We compared the cone beam computed tomography (CBCT) and micro-computed tomography (micro-CT) scans of extracted mandibular incisors to check the accuracy of morphological measurements. Thereafter, the root canal morphology and aging-related changes in the mandibular incisors of Japanese individuals were assessed using CBCT. Six extracted teeth were fixed in a phantom head and imaged using CBCT and micro-CT. The correlation between the findings of the two imaging modalities was examined. Further, CBCT reconstructed images of the mandibular incisors of 81 individuals were observed. Age-related changes of the root canals were compared between participants aged <30 years and those aged ≤30 years. The CBCT and micro-CT findings regarding the root canals of the extracted teeth coincided in 94.4% of the cases. Mandibular incisors exhibiting two root canals in either cross-section accounted for 9.9% of central incisors and 12.4% of lateral incisors. Mandibular central incisors with two root canals were observed in two (6.3%) individuals aged <30 years and six (12.2%) aged ≤30 years. Mandibular lateral incisors with two root canals were observed in one (3.1%) individual aged <30 years and nine (18.4%) aged ≤30 years. CBCT allows accurate evaluation of complex root canal morphologies and is useful for endodontic preoperative assessment. Mandibular incisors have more frequent occurrence of two root canals with aging. [ABSTRACT FROM AUTHOR]

Cone-beam computed tomography (CBCT) can provide 3D images of a targeted area with the advantage of lower dosage than multidetector computed tomography (MDCT; also simply referred to as CT). However, in CBCT, due to the cone-shaped geometry of the X-ray source and the absence of post-patient collimation, the presence of more scattering rays deteriorates the image quality compared with MDCT. CBCT is commonly used in dental clinics, and image artifacts negatively affect the radiology workflow and diagnosis. Studies have attempted to eliminate image artifacts and improve image quality; however, a vast majority of that work sacrificed structural details of the image. The current study presents a novel approach to reduce image artifacts while preserving details and sharpness in the original CBCT image for precise diagnostic purposes. We used MDCT images as reference high-quality images. Pairs of CBCT and MDCT scans were collected retrospectively at a university hospital, followed by co-registration between the CBCT and MDCT images. A contextual loss-optimized multi-planar 2.5D U-Net was proposed. Images corrected using this model were evaluated quantitatively and qualitatively by dental clinicians. The quantitative metrics showed superior quality in output images compared to the original CBCT. In the qualitative evaluation, the generated images presented significantly higher scores for artifacts, noise, resolution, and overall image quality. This proposed novel approach for noise and artifact reduction with sharpness preservation in CBCT suggests the potential of this method for diagnostic imaging. [ABSTRACT FROM AUTHOR]

Human identification is considered as an important step in the reconstruction of biological profiles, especially of unknown individuals. Frontal sinuses (FS) have been regarded as an ideal anatomical structure for individualisation because few pathological conditions can potentially alter their shape. Aim: The aim of this review was to evaluate scientific evidence published since January 2010 and determine whether the dimensions and volume of FS might be useful parameters for gender determination and human identification, based only on cone beam computed tomography images (CBCT). Methods: This review was performed in accordance with the PRISMA statement. Four databases were searched for articles published between January 2010 and June 2022. Results: A total of 195 records were initially identified, and 90 remained after a manual duplicate check. Eight articles were selected for a full review according to the inclusion and exclusion criteria after title and abstract screening. A total of 718 participants (359 males and 359 females) were identified from the included studies. Frontal sinus volume (FSV) was significantly higher in male individuals. Frontal sinus height (FSH) and volume were the superior discriminating parameters for forensic identification. Conclusions: This review demonstrates that assessment of FS based on CBCT images could be beneficial for gender identification in forensic science. According to the obtained studies, frontal sinus volume (FSV) and frontal sinus height (FSH) are significant greater in males than in females, providing an additional complementary method. Larger sample size and common measurement protocols are needed to verify their usefulness. [ABSTRACT FROM AUTHOR]

Research exploring CycleGAN-based synthetic image generation has recently accelerated in the medical community due to its ability to leverage unpaired images effectively. However, a commonly established drawback of the CycleGAN, the introduction of artifacts in generated images, makes it unreliable for medical imaging use cases. In an attempt to address this, we explore the effect of structure losses on the CycleGAN and propose a generalized frequency-based loss that aims at preserving the content in the frequency domain. We apply this loss to the use-case of cone-beam computed tomography (CBCT) translation to computed tomography (CT)-like quality. Synthetic CT (sCT) images generated from our methods are compared against baseline CycleGAN along with other existing structure losses proposed in the literature. Our methods (MAE: 85.5, MSE: 20433, NMSE: 0.026, PSNR: 30.02, SSIM: 0.935) quantitatively and qualitatively improve over the baseline CycleGAN (MAE: 88.8, MSE: 24244, NMSE: 0.03, PSNR: 29.37, SSIM: 0.935) across all investigated metrics and are more robust than existing methods. Furthermore, no observable artifacts or loss in image quality were observed. Finally, we demonstrated that sCTs generated using our methods have superior performance compared to the original CBCT images on selected downstream tasks. [ABSTRACT FROM AUTHOR]

In outdoor environments or environments with space restrictions, it is difficult to transport and use conventional computed tomography (CT) systems. Therefore, there is an urgent need for rapid reconstruction of portable cone-beam CT (CBCT) systems. However, owing to its portability and the characteristics of temporary construction environments, high precision spatial location is difficult to achieve with portable CBCT systems. To overcome these limitations, we propose an iterative self-calibration improvement method with a self-calculated initial value based on the projection relationship and image features. The CT value of an open field image was used as the weight value of the projection data in the subsequent experiments to reduce the nonlinear attenuation of the projection intensity. Subsequently, an initial value was obtained based on the invariance of the rotation axis. Finally, self-calibration was realized iteratively using the reconstructed image. This method overcomes the main problem of the rotation axis invariance calibration algorithm—high similarity between the adjacent positions of symmetrical homogeneous materials. The proposed method not only improves the precision of self-calibration based on the projection relationship, but also reduces the performance cost and solution time of the self-calibration algorithm based on the image features. Thus, it satisfies the precision requirements for self-calibration of portable CBCT systems. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to demonstrate the potential utility of cone‐beam computed tomography (CBCT)‐guided online adaptive radiotherapy (ART) under end‐exhalation breath‐hold (EE‐BH) conditions for pancreatic cancer (PC). Methods: Eleven PC patients who underwent 15‐fraction volumetric‐modulated arc therapy under EE‐BH conditions were included. Planning CT images and daily 165 CBCT images were imported into a dedicated treatment planning system. The prescription dose was set to 48 Gy in 15 fractions. The reference plan was automatically generated along with predefined clinical goals. After segmentation was completed on CBCT images, two different plans were generated: One was an adapted (ADP) plan in which re‐optimization was performed on the anatomy of the day, and the other was a scheduled (SCH) plan, which was the same as the reference plan. The dose distributions calculated using the synthetic CT created from both planning CT and CBCT were compared between the two plans. Independent calculation‐based quality assurance was also performed for the ADP plans, with a gamma passing rate of 3%/3 mm. Results: All clinical goals were successfully achieved during the reference plan generation. Of the 165 sessions, gross tumor volume D98% and clinical target volume D98% were higher in 100 (60.1%) and 122 (74.0%) ADP fractions. In each fraction, the V3 Gy < 1 cm3 of the stomach and duodenum was violated in 47 (28.5%) and 48 (29.1%), respectively, of the SCH fractions, whereas no violations were observed in the ADP fractions. There were statistically significant differences in the dose–volume indices between the SCH and ADP fractions (p < 0.05). The gamma passing rates were above 95% in all ADP fractions. Conclusions: The CBCT‐guided online ART under EE‐BH conditions successfully reduced the dose to the stomach and duodenum while maintaining target coverage. [ABSTRACT FROM AUTHOR]

This study assesses the accuracy and technical predictability of a computer-guided procedure for harvesting bone from the external oblique ridge using a patient-specific cutting guide. Twenty-two patients needing bone augmentation for implant placement were subjected to mandibular osteotomy employing a case-specific stereolithographic surgical guide generated through computer aided design. Differences between planned and real cut planes were measured comparing pre- and post-operative Cone Beam Computed Tomography images of the donor site according to six validated angular and displacement indexes. Accuracy and technical predictability were assessed for 119 osteotomy planes over the study population. Three different guide fitting approaches were compared. An average root-mean-square discrepancy of 0.52 (0.30–0.97) mm was detected. The accuracy of apical and medial planes was higher than the mesial and distal planes due to occasional antero-posterior guide shift. Fitting the guide with an extra reference point on the closest tooth performed better than using only the bone surface, with two indexes significantly lower and less disperse. The study showed that the surgical plan was actualized with a 1 mm safety margin, allowing effective nerve preservation and reducing technical variability. When possible, surgical guide design should allow fitting on the closest tooth based on both radiological and/or intra-oral scan data. [ABSTRACT FROM AUTHOR]

Online adaptive radiotherapy platforms present a unique challenge for commissioning as guidance is lacking and specialized adaptive equipment, such as deformable phantoms, are rare. We designed a novel adaptive commissioning process consisting of end‐to‐end tests using standard clinical resources. These tests were designed to simulate anatomical changes regularly observed at patient treatments. The test results will inform users of the magnitude of uncertainty from on‐treatment changes during the adaptive workflow and the limitations of their systems. We implemented these tests for the cone‐beam computed tomography (CT)‐based Varian Ethos online adaptive platform. Many adaptive platforms perform online dose calculation on a synthetic CT (synCT). To assess the impact of the synCT generation and online dose calculation on dosimetric accuracy, we conducted end‐to‐end tests using commonly available equipment: a CIRS IMRT Thorax phantom, PinPoint ionization chamber, Gafchromic film, and bolus. Four clinical scenarios were evaluated: weight gain and weight loss were simulated by adding and removing bolus, internal target shifts were simulated by editing the CTV during the adaptive workflow to displace it, and changes in gas were simulated by removing and reinserting rods in varying phantom locations. The effect of overriding gas pockets during planning was also assessed. All point dose measurements agreed within 2.7% of the calculated dose, with one exception: a scenario simulating gas present in the planning CT, not overridden during planning, and dissipating at treatment. Relative film measurements passed gamma analysis (3%/3 mm criteria) for all scenarios. Our process validated the Ethos dose calculation for online adapted treatment plans. Based on our results, we made several recommendations for our clinical adaptive workflow. This commissioning process used commonly available equipment and, therefore, can be applied in other clinics for their respective online adaptive platforms. [ABSTRACT FROM AUTHOR]

Cone-beam computed tomography (CBCT) has been shown to be a powerful tool for 3D imaging of the appendicular skeleton, allowing for detailed visualization of bone microarchitecture. This study was designed to compare artifacts in the presence of osteosynthetic implants between CBCT and multidetector computed tomography (MDCT) in cadaveric wrist scans. A total of 32 scan protocols with varying tube potential and current were employed: both conventional CBCT and MDCT studies were included with tube voltage ranging from 60 to 140 kVp as well as additional MDCT protocols with dedicated spectral shaping via tin prefiltration. Irrespective of scanner type, all examinations were conducted in ultra-high-resolution (UHR) scan mode. For reconstruction of UHR-CBCT scans an additional iterative metal artifact reduction algorithm was employed, an image correction tool which cannot be used in combination with UHR-MDCT. To compare applied radiation doses between both scanners, the volume computed tomography dose index for a 16 cm phantom (CTDIvol) was evaluated. Images were assessed regarding subjective and objective image quality. Without automatic tube current modulation or tube potential control, radiation doses ranged between 1.3 mGy (with 70 kVp and 50.0 effective mAs) and 75.2 mGy (with 140 kVp and 383.0 effective mAs) in UHR-MDCT. Using the pulsed image acquisition method of the CBCT scanner, CTDIvol ranged between 2.3 mGy (with 60 kVp and 0.6 mean mAs per pulse) and 61.0 mGy (with 133 kVp and 2.5 mean mAs per pulse). In essence, all UHR-CBCT protocols employing a tube potential of 80 kVp or more were found to provide superior overall image quality and artifact reduction compared to UHR-MDCT (all p <.050). Interrater reliability of seven radiologists regarding image quality was substantial for tissue assessment and moderate for artifact assessment with Fleiss kappa of 0.652 (95% confidence interval 0.618–0.686; p < 0.001) and 0.570 (95% confidence interval 0.535–0.606; p < 0.001), respectively. Our results demonstrate that the UHR-CBCT scan mode of a twin robotic X-ray system facilitates excellent visualization of the appendicular skeleton in the presence of metal implants. Achievable image quality and artifact reduction are superior to dose-comparable UHR-MDCT and even MDCT protocols employing spectral shaping with tin prefiltration do not achieve the same level of artifact reduction in adjacent soft tissue. [ABSTRACT FROM AUTHOR]

Reducing radiation dose to patients without compromising imaging quality has been an important issue in the medical use of X-ray computed tomography (CT). In this study, based on the conceptual designs of different types of attenuation filters, the radiation doses to patients who undergo a typical head, thorax and abdomen scan using a cone-beam CT with different scanning protocols were simulated using the Monte Carlo method, and the isotropy of the noise power spectrum (NPS) of the reconstructed images was also calculated. Compared to the scanning protocol without attenuation and tube current modulation (TCM), the results showed that the fluid dynamic bowtie filter (FDB) combined with the TCM technique reduced the average organ dose by 70%, 34% and 60% for a typical head, thorax and abdomen scan, respectively, and the NPS isotropy of the reconstructed images was also significantly improved. Compared to most currently used static bowtie filters, the FDB has a higher potential to reduce the dose for patients undergoing CT scans. Further efforts are warranted to make the FDB technique clinically useful. [ABSTRACT FROM AUTHOR]

Background: Iterative reconstruction for cone-beam computed tomography (CBCT) has been applied to improve image quality and reduce radiation dose. In a case where an object's actual projection is larger than a flat panel detector, CBCT images contain truncated data or incomplete projections, which degrade image quality inside the field of view (FOV). In this work, we propose truncation effect reduction for fast iterative reconstruction in CBCT imaging. Methods: The volume matrix size of the FOV and the height of projection images were extrapolated to a suitable size. These extended projections were reconstructed by fast iterative reconstruction. Moreover, a smoothing parameter for noise regularization in iterative reconstruction was modified to reduce the accumulated error while processing. The proposed work was evaluated by image quality measurements and compared with conventional filtered backprojection (FBP). To validate the proposed method, we used a head phantom for evaluation and preliminarily tested on a human dataset. Results: In the experimental results, the reconstructed images from the head phantom showed enhanced image quality. In addition, fast iterative reconstruction can be run continuously while maintaining a consistent mean-percentage-error value for many iterations. The contrast-to-noise ratio of the soft-tissue images was improved. Visualization of low contrast in the ventricle and soft-tissue images was much improved compared to those from FBP using the same dose index of 5 mGy. Conclusions: Our proposed method showed satisfactory performance to reduce the truncation effect, especially inside the FOV with better image quality for soft-tissue imaging. The convergence of fast iterative reconstruction tends to be stable for many iterations. [ABSTRACT FROM AUTHOR]

Spectral CT has shown promise for high-sensitivity quantitative imaging and material decomposition. This work presents a new device called a spatial-spectral filter (SSF) which consists of a tiled array of filter materials positioned near the x-ray source that is used to modulate the spectral shape of the x-ray beam. The filter is moved to obtain projection data that is sparse in each spectral channel. To process this sparse data, we employ a one-step direct model-based material decomposition (MBMD) to reconstruct basis material density images directly from the SSF CT data. To evaluate different possible SSF designs, we define a new Fisher-information-based predictive image quality metric called separability index which characterizes the ability of a spectral CT system to distinguish between the signals from two or more materials. This spectral CT performance metric can be used to optimize spectral CT system design. We conducted simulation-based design optimization study to find optimized combinations of filter materials, filter thicknesses, filter widths, and source settings. Finally, we present MBMD results using simulated SSF CT measurements from the optimized designs to demonstrate the ability to reconstruct basis material density images and to show the benefits of the optimized designs. Our results indicate that optimizing SSF CT for separability leads to high-performance at material discrimination tasks. [ABSTRACT FROM AUTHOR]

Modern cone-beam CT systems are capable of ultra-high-resolution 3D imaging in addition to conventional radiography and fluoroscopy. The combination of various imaging functions in a multi-use setup is particularly appealing for musculoskeletal interventions, such as CBCT arthrography (CBCTA). With this study, we aimed to investigate the feasibility of CBCTA of the wrist in a "one-stop-shop" approach with a gantry-free twin robotic scanner that does not require repositioning of subjects. Additionally, the image quality of CBCTA was compared to subsequent arthrograms on a high-end multidetector CT (MDCTA). Fourteen cadaveric wrists received CBCTA with four acquisition protocols. Specimens were then transferred to the CT suite for additional MDCTA. Dose indices ranged between 14.3 mGy (120 kVp/100 effective mAs; full-dose) and 1.0 mGy (70 kVp/41 effective mAs; ultra-low-dose) for MDCTA and between 17.4 mGy (80 kVp/2.5 mAs per pulse; full-dose) and 1.2 mGy (60 kVp/0.5 mAs per pulse; ultra-low-dose) for CBCTA. Subjective image quality assessment for bone, cartilage and ligamentous tissue was performed by seven radiologists. The interrater reliability was assessed by calculation of the intraclass correlation coefficient (ICC) based on a two-way random effects model. Overall image quality of most CBCTA was deemed suitable for diagnostic use in contrast to a considerable amount of non-diagnostic MDCTA examinations (38.8%). The depiction of bone, cartilage and ligaments in MDCTA with any form of dose reduction was inferior to any CBCTA scan with at least 0.6 mAs per pulse (all p < 0.001). Full-dose MDCTA and low-dose CBCTA were of equal quality for bone tissue visualization (p = 0.326), whereas CBCTA allowed for better depiction of ligaments and cartilage (both p < 0.001), despite merely one third of radiation exposure (MDCTA–14.3 mGy vs. CBCTA–4.5 mGy). Moderate to good interrater reliability was ascertained for the assessment all tissues (ICC 0.689–0.756). Overall median examination time for CBCTA was 5.4 min (4.8–7.2 min). This work demonstrates that substantial dose reduction can be achieved in CT arthrography of the wrist while maintaining diagnostic image quality by employing the cone-beam CT mode of a twin robotic X-ray system. The ability of the multi-use X-ray system to switch between fluoroscopy mode and 3D imaging allows for "one-stop-shop" CBCTA in minimal examination time without the need for repositioning. [ABSTRACT FROM AUTHOR]

Iodine contrast agent is widely used in liver cancer radiotherapy at CT simulation stage to enhance detectability of tumor. However, its application in cone beam CT (CBCT) for image guidance before treatment delivery is still limited because of poor image quality and excessive dose of contrast agent during multiple treatment fractions. We previously developed a multienergy element-resolved (MEER) CBCT framework that included x-ray projection data acquisition on a conventional CBCT platform in a kVp-switching model and a dictionary-based image reconstruction algorithm that simultaneously reconstructed x-ray attenuation images at each kilovoltage peak (kVp), an electron density image, and elemental composition images. In this study, we investigated feasibility using MEER-CBCT for low-concentration iodine contrast agent visualization. We performed simulation and experimental studies using a phantom with inserts containing water and different concentrations of iodine solution and the MEER-CBCT scan with 600 projections in a full gantry rotation, in which the kVp level sequentially changed among 80, 100, and 120 kVps. We included iodine material in the dictionary of the reconstruction algorithm. We analyzed iodine detectability as quantified by contrast-to-noise ratio (CNR) and compared results with those of CBCT images reconstructed by the standard filter back projection (FBP) method with 600 projections. MEER-CBCT achieved similar contrast enhancement as FBP method but significantly higher CNR. At 2.5% iodine solution concentration, FBP method achieved 170 HU enhancement and CNR of 2.0, considered the standard CNR for successful tumor visualization. MEER-CBCT achieved the same CNR but at ~6.3 times lower iodine concentration of 0.4%. [ABSTRACT FROM AUTHOR]

Background: Reconstruction of high quality two dimensional images from fan beam computed tomography (CT) with a limited number of projections is already feasible through Fourier based iterative reconstruction method. However, this article is focused on a more complicated reconstruction of three dimensional (3D) images in a sparse view cone beam computed tomography (CBCT) by utilizing Compressive Sensing (CS) based on 3D pseudo polar Fourier transform (PPFT). Method: In comparison with the prevalent Cartesian grid, PPFT re gridding is potent to remove rebinning and interpolation errors. Furthermore, using PPFT based radon transform as the measurement matrix, reduced the computational complexity. Results: In order to show the computational efficiency of the proposed method, we compare it with an algebraic reconstruction technique and a CS type algorithm. We observed convergence in <20 iterations in our algorithm while others would need at least 50 iterations for reconstructing a qualified phantom image. Furthermore, using a fast composite splitting algorithm solver in each iteration makes it a fast CBCT reconstruction algorithm. The algorithm will minimize a linear combination of three terms corresponding to a least square data fitting, Hessian (HS) Penalty and l1 norm wavelet regularization. We named it PP-based compressed sensing-HS-W. In the reconstruction range of 120 projections around the 360° rotation, the image quality is visually similar to reconstructed images by Feldkamp-Davis-Kress algorithm using 720 projections. This represents a high dose reduction. Conclusion: The main achievements of this work are to reduce the radiation dose without degrading the image quality. Its ability in removing the staircase effect, preserving edges and regions with smooth intensity transition, and producing high-resolution, low-noise reconstruction results in low-dose level are also shown. [ABSTRACT FROM AUTHOR]

Data truncation is a common problem in computed tomography (CT). Truncation causes cupping artifacts inside the field-of-view (FOV) and anatomical structures missing outside the FOV. Deep learning has achieved impressive results in CT reconstruction from limited data. However, its robustness is still a concern for clinical applications. Although the image quality of learning-based compensation schemes may be inadequate for clinical diagnosis, they can provide prior information for more accurate extrapolation than conventional heuristic extrapolation methods. With extrapolated projection, a conventional image reconstruction algorithm can be applied to obtain a final reconstruction. In this work, a general plug-and-play (PnP) method for truncation correction is proposed based on this idea, where various deep learning methods and conventional reconstruction algorithms can be plugged in. Such a PnP method integrates data consistency for measured data and learned prior image information for truncated data. This shows to have better robustness and interpretability than deep learning only. To demonstrate the efficacy of the proposed PnP method, two state-of-the-art deep learning methods, FBPConvNet and Pix2pixGAN, are investigated for truncation correction in cone-beam CT in noise-free and noisy cases. Their robustness is evaluated by showing false negative and false positive lesion cases. With our proposed PnP method, false lesion structures are corrected for both deep learning methods. For FBPConvNet, the root-mean-square error (RMSE) inside the FOV can be improved from 92HU to around 30HU by PnP in the noisy case. Pix2pixGAN solely achieves better image quality than FBPConvNet solely for truncation correction in general. PnP further improves the RMSE inside the FOV from 42HU to around 27HU for Pix2pixGAN. The efficacy of PnP is also demonstrated on real clinical head data. [ABSTRACT FROM AUTHOR]

Cone-beam computed tomography is a powerful tool for 3D imaging of the appendicular skeleton, facilitating detailed visualization of bone microarchitecture. This study evaluated various combinations of acquisition and reconstruction parameters for the cone-beam CT mode of a twin robotic x-ray system in cadaveric wrist and elbow scans, aiming to define the best possible trade-off between image quality and radiation dose. Images were acquired with different combinations of tube voltage and tube current–time product, resulting in five scan protocols with varying volume CT dose indices: full-dose (FD; 17.4 mGy), low-dose (LD; 4.5 mGy), ultra-low-dose (ULD; 1.15 mGy), modulated low-dose (mLD; 0.6 mGy) and modulated ultra-low-dose (mULD; 0.29 mGy). Each set of projection data was reconstructed with three convolution kernels (very sharp [Ur77], sharp [Br69], intermediate [Br62]). Five radiologists subjectively assessed the image quality of cortical bone, cancellous bone and soft tissue using seven-point scales. Irrespective of the reconstruction kernel, overall image quality of every FD, LD and ULD scan was deemed suitable for diagnostic use in contrast to mLD (very sharp/sharp/intermediate: 60/55/70%) and mULD (0/3/5%). Superior depiction of cortical and cancellous bone was achieved in FDUr77 and LDUr77 examinations (p < 0.001) with LDUr77 scans also providing favorable bone visualization compared to FDBr69 and FDBr62 (p < 0.001). Fleiss' kappa was 0.618 (0.594–0.641; p < 0.001), indicating substantial interrater reliability. In this study, we demonstrate that considerable dose reduction can be realized while maintaining diagnostic image quality in upper extremity joint scans with the cone-beam CT mode of a twin robotic x-ray system. Application of sharper convolution kernels for image reconstruction facilitates superior display of bone microarchitecture. [ABSTRACT FROM AUTHOR]

Background: Estimation of eye lens dose is important in head computed tomography (CT) examination since the eye lens is a sensitive organ to ionizing radiation. Objective: The purpose of this study is to compare estimations of eye lens dose in head CT examinations using local size-specific dose estimate (SSDE) based on size-conversion factors of the American Association of Physicists in Medicine (AAPM) Report No. 293 with those based on size-conversion factors of the AAPM Report No. 220. Material and Methods: This experimental study is conducted on a group of patients who had undergone nasopharyngeal CT examination. Due to the longitudinal (z-axis) dose fluctuation, the average global SSDE and average local SSDE (i.e. particular slices where the eyes are located) were investigated. All estimates were compared to the measurement results using thermo-luminescent dosimeters (TLDs). The estimated and measured doses were implemented for 14 patients undergoing nasopharyngeal CT examination. Results: It was found that the percentage differences of the volume CT dose index (CTDIvol), average global SSDE based on AAPM No. 220 (SSDEo,g), average local SSDE based on AAPM No. 220 (SSDEo,l), average global SSDE based on AAPM No. 293 (SSDEn,g) and average local SSDE based on AAPM No. 293 (SSDEn,l) against the measured TLD doses were 22.5, 21.7, 15.0, 9.3, and 2.1%, respectively. All comparisons between dose estimates and TLD measurements gave p-values less than 0.001, except for SSDEn,l (p-value = 0.566). Conclusion: SSDE based on AAPM Report No. 293 can be used to accurately estimate eye lens radiation doses by performing the calculations on a number of specific slices containing the eyes. [ABSTRACT FROM AUTHOR]

Among many of the image reconstruction techniques; the Feldkamp-Davis-Kress (FDK) is considered the most practical algorithm that used in clinical cone-beam Computed Tomography (CT) technology. In this paper, we present a full memory-aware management optimization scheme to reconstruct high-resolution volumes for a large number of X-Ray images as projections based on an efficient GPU acceleration technique. The proposed optimization technique is a scheme for FDK acceleration, that sheds new light on 4 new strategies: (1) Overcome limited device memory by evaluating different four configurations to migrate input and output data in the CPU/GPU system, (2) Reduce data transfer time during the FDK execution by using a Unified Memory (UM) model with data prefetching feature during reconstruction for data migration between host and device, (3) Accelerate the bottleneck algorithm back-projection as a result of computation mitigation, and (4) Optimize projection data layout that led to better device memory access and overcomes memory latency problem before processing and computing on GPU. The experimental results based on the proposed method show that it took 21.17 sec and 101.76 sec to reconstruct high-resolution 1024 3 , 2048 3 - voxel volume from 1800 projection of 1024 2 and 2048 2 -pixel respectively. The performance resulted from our optimization technique considered on-the-fly reconstruction (real-time), which means it can process 85 projections per second for high-resolution volumes from a large number of projections to achieve accuracy and resolution for reconstructed volume. In the term of speedup, the proposed method can achieve 1.72 speedup to reconstruct the low-resolution volume 512 3 , 1.82 speedup for 1024 3 volume and 1.70 s p e e d u p f o r 2048 3 for highest resolution volumes over baseline implementation and optimized over previous reconstruction methods based on FDK. [ABSTRACT FROM AUTHOR]

Cone-beam dental CT can provide high-precision 3D images of the teeth and surrounding bones. From the 3D CT images, 3D models, also called digital impressions, can be computed for CAD/CAM-based fabrication of dental restorations or orthodontic devices. However, the cone-beam angle-dependent artifacts, mostly caused by the incompleteness of the projection data acquired in the circular cone-beam scan geometry, can induce significant errors in the 3D models. Using a micro-CT, we acquired CT projection data of plaster cast models at several different cone-beam angles, and we investigated the dependency of the model errors on the cone-beam angle in comparison with the reference models obtained from the optical scanning of the plaster models. For the 3D CT image reconstruction, we used the conventional Feldkamp algorithm and the combined half-scan image reconstruction algorithm to investigate the dependency of the model errors on the image reconstruction algorithm. We analyzed the mean of positive deviations and the mean of negative deviations of the surface points on the CT-image-derived 3D models from the reference model, and we compared them between the two image reconstruction algorithms. It has been found that the model error increases as the cone-beam angle increases in both algorithms. However, the model errors are smaller in the combined half-scan image reconstruction when the cone-beam angle is as large as 10 degrees. [ABSTRACT FROM AUTHOR]

In this paper, we establish a procedure for the enhancement of cone-beam computed tomography (CBCT) dental-maxillofacial images; this can be useful in order to face the problem of rapid prototyping, i.e., to generate a 3D printable file of a dental prosthesis. In the proposed procedure, a crucial role is played by the so-called sampling Kantorovich (SK) algorithm for the reconstruction and image noise reduction. For the latter algorithm, it has already been shown to be effective in the reconstruction and enhancement of real-world images affected by noise in connection to engineering and biomedical problems. The SK algorithm is given by an optimized implementation of the well-known sampling Kantorovich operators and their approximation properties. A comparison between CBTC images processed by the SK algorithm and other well-known methods of digital image processing known in the literature is also given. We finally remark that the above-treated topic has a strong multidisciplinary nature and involves concrete biomedical applications of mathematics. In this type of research, theoretical and experimental disciplines merge in order to find solutions to real-world problems. [ABSTRACT FROM AUTHOR]