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We investigate the impact of a conventional corporate taxation system on an investment project's profitability and risk and on a firm's risk diversification capability. We use the Canadian corporate tax system as a representative of Western countries' conventional non-neutral corporate taxation systems and contrast it with a neutral taxation system. The analysis uses a simple probabilistic NPV stationary model with normally distributed random errors. We show that corporate taxation is doubly regressive, in that both the effective tax rate and the riskiness of a project decrease as its return on investment increases. Diversification capabilities also can be impaired or improved by the conventional non-neutral taxation system. [ABSTRACT FROM AUTHOR]

Background: Synovitis is one of the defining characteristics of osteoarthritis (OA) in the carpometacarpal (CMC1) joint of the thumb. Quantitative characterization of synovial volume is important for furthering our understanding of CMC1 OA disease progression, treatment response, and monitoring strategies. In previous studies, three‐dimensional ultrasound (3‐D US) has demonstrated the feasibility of being a point‐of‐care system for monitoring knee OA. However, 3‐D US has not been tested on the smaller joints of the hand, which presents unique physiological and imaging challenges. Purpose: To develop and validate a novel application of 3‐D US to monitor soft‐tissue characteristics of OA in a CMC1 OA patient population compared to the current gold standard, magnetic resonance imaging (MRI). Methods: A motorized submerged transducer moving assembly was designed for this device specifically for imaging the joints of the hands and wrist. The device used a linear 3‐D scanning approach, where a 14L5 2‐D transducer was translated over the region of interest. Two imaging phantoms were used to test the linear and volumetric measurement accuracy of the 3‐D US device. To evaluate the accuracy of the reconstructed 3‐D US geometry, a multilayer monofilament string‐grid phantom (10 mm square grid) was scanned. To validate the volumetric measurement capabilities of the system, a simulated synovial tissue phantom with an embedded synovial effusion was fabricated and imaged. Ten CMC1 OA patients were imaged by our 3‐D US and a 3.0 T MRI system to compare synovial volumes. The synovial volumes were manually segmented by two raters on the 2D slices of the 3D US reconstruction and MR images, to assess the accuracy and precision of the device for determining synovial tissue volumes. The Standard Error of Measurement and Minimal Detectable Change was used to assess the precision and sensitivity of the volume measurements. Paired sample t‐tests were used to assess statistical significance. Additionally, rater reliability was assessed using Intra‐Class Correlation (ICC) coefficients. Results: The largest percent difference observed between the known physical volume of synovial extrusion in the phantom and the volume measured by our 3D US was 1.1% (p‐value = 0.03). The mean volume difference between the 3‐D US and the gold standard MRI was 1.78% (p‐value = 0.48). The 3‐D US synovial tissue volume measurements had a Standard Error Measurement (SEm) of 11.21 mm3 and a Minimal Detectible Change (MDC) of 31.06 mm3, while the MRI synovial tissue volume measurements had an SEM of 16.82 mm3 and an MDC of 46.63 mm3. Excellent inter‐ and intra‐rater reliability (ICCs = 0.94–0.99) observed across all imaging modalities and raters. Conclusion: Our results indicate the feasibility of applying 3‐D US technology to provide accurate and precise CMC1 synovial tissue volume measurements, similar to MRI volume measurements. Lower MDC and SEm values for 3‐D US volume measurements indicate that it is a precise measurement tool to assess synovial volume and that it is sensitive to variation between volume segmentations. The application of this imaging technique to monitor OA pathogenesis and treatment response over time at the patient's bedside should be thoroughly investigated in future studies. [ABSTRACT FROM AUTHOR]

Background: Multiparametric MRI (mpMRI) is an effective tool for detecting and staging prostate cancer (PCa), guiding interventional therapy, and monitoring PCa treatment outcomes. MRI-guided focal laser ablation (FLA) therapy is an alternative, minimally invasive treatment method to conventional therapies, which has been demonstrated to control low-grade, localized PCa while preserving patient quality of life. The therapeutic success of FLA depends on the accurate placement of needles for adequate delivery of ablative energy to the target lesion.We previously developed an MR-compatible mechatronic system for prostate FLA needle guidance and validated its performance in open-air and clinical 3T in-bore experiments using virtual targets. Purpose: To develop a robust MRI-to-mechatronic system registration method and evaluate its in-bore MR-guided needle delivery accuracy in tissue-mimicking prostate phantoms. Methods: The improved registration multifiducial assembly houses thirty-six aqueous gadolinium-filled spheres distributed over a 7.3 × 7.3 × 5.2 cm volume. MRI-guided needle guidance accuracy was quantified in agar-based tissue-mimicking prostate phantoms on trajectories (N = 44) to virtual targets covering the mechatronic system’s range of motion. 3T gradient-echo recalled (GRE) MRI images were acquired after needle insertions to each target, and the airfilled needle tracks were segmented. Needle guidance error was measured as the shortest Euclidean distance between the target point and the segmented needle trajectory, and angular error was measured as the angle between the targeted trajectory and the segmented needle trajectory. These measurements were made using both the previously designed four-sphere registration fiducial assembly on trajectories (N = 7) and compared with the improved multifiducial assembly using a Mann–Whitney U test. Results: The median needle guidance error of the system using the improved registration fiducial assembly at a depth of 10 cm was 1.02 mm with an interquartile range (IQR) of 0.42–2.94 mm.The upper limit of the one-sided 95% prediction interval of needle guidance error was 4.13 mm. The median (IQR) angular error was 0.0097 rad (0.0057–0.015 rad) with a one-sided 95% prediction interval upper limit of 0.022 rad. The median (IQR) positioning error using the previous four-sphere registration fiducial assembly was 1.87 mm (1.77–2.14 mm). This was found to be significantly different (p = 0.0012) from the median (IQR) positioning error of 0.28 mm (0.14–0.95 mm) using the new registration fiducial assembly on the same trajectories. No significant difference was detected between the medians of the angular errors (p = 0.26). Conclusion: This is the first study presenting an improved registration method and validation in tissue-mimicking phantoms of our remotely actuated Med Phys. MR-compatible mechatronic system for delivery of prostate FLA needles. Accounting for the effects of needle deflection, the system was demonstrated to be capable of needle delivery with an error of 4.13 mm or less in 95% of cases under ideal conditions, which is a statistically significant improvement over the previous method. The system will next be validated in a clinical setting. [ABSTRACT FROM AUTHOR]

Background: Mammographic screening has reduced mortality in women through the early detection of breast cancer. However, the sensitivity for breast cancer detection is significantly reduced in women with dense breasts, in addition to being an independent risk factor. Ultrasound (US) has been proven effective in detecting small, early‐stage, and invasive cancers in women with dense breasts. Purpose: To develop an alternative, versatile, and cost‐effective spatially tracked three‐dimensional (3D) US system for whole‐breast imaging. This paper describes the design, development, and validation of the spatially tracked 3DUS system, including its components for spatial tracking, multi‐image registration and fusion, feasibility for whole‐breast 3DUS imaging and multi‐planar visualization in tissue‐mimicking phantoms, and a proof‐of‐concept healthy volunteer study. Methods: The spatially tracked 3DUS system contains (a) a six‐axis manipulator and counterbalanced stabilizer, (b) an in‐house quick‐release 3DUS scanner, adaptable to any commercially available US system, and removable, allowing for handheld 3DUS acquisition and two‐dimensional US imaging, and (c) custom software for 3D tracking, 3DUS reconstruction, visualization, and spatial‐based multi‐image registration and fusion of 3DUS images for whole‐breast imaging. Spatial tracking of the 3D position and orientation of the system and its joints (J1–6) were evaluated in a clinically accessible workspace for bedside point‐of‐care (POC) imaging. Multi‐image registration and fusion of acquired 3DUS images were assessed with a quadrants‐based protocol in tissue‐mimicking phantoms and the target registration error (TRE) was quantified. Whole‐breast 3DUS imaging and multi‐planar visualization were evaluated with a tissue‐mimicking breast phantom. Feasibility for spatially tracked whole‐breast 3DUS imaging was assessed in a proof‐of‐concept healthy male and female volunteer study. Results: Mean tracking errors were 0.87 ± 0.52, 0.70 ± 0.46, 0.53 ± 0.48, 0.34 ± 0.32, 0.43 ± 0.28, and 0.78 ± 0.54 mm for joints J1–6, respectively. Lookup table (LUT) corrections minimized the error in joints J1, J2, and J5. Compound motions exercising all joints simultaneously resulted in a mean tracking error of 1.08 ± 0.88 mm (N = 20) within the overall workspace for bedside 3DUS imaging. Multi‐image registration and fusion of two acquired 3DUS images resulted in a mean TRE of 1.28 ± 0.10 mm. Whole‐breast 3DUS imaging and multi‐planar visualization in axial, sagittal, and coronal views were demonstrated with the tissue‐mimicking breast phantom. The feasibility of the whole‐breast 3DUS approach was demonstrated in healthy male and female volunteers. In the male volunteer, the high‐resolution whole‐breast 3DUS acquisition protocol was optimized without the added complexities of curvature and tissue deformations. With small post‐acquisition corrections for motion, whole‐breast 3DUS imaging was performed on the healthy female volunteer showing relevant anatomical structures and details. Conclusions: Our spatially tracked 3DUS system shows potential utility as an alternative, accurate, and feasible whole‐breast approach with the capability for bedside POC imaging. Future work is focused on reducing misregistration errors due to motion and tissue deformations, to develop a robust spatially tracked whole‐breast 3DUS acquisition protocol, then exploring its clinical utility for screening high‐risk women with dense breasts. [ABSTRACT FROM AUTHOR]

Purpose: Prostate cancer is the most common non‐cutaneous cancer among men in the United States and is the second leading cause of cancer death in American men. (Siegel et al. [2019] CA: A Cancer J Clin.69(1):7‐34.) Focal laser ablation (FLA) has the potential to control small tumors while preserving urinary and erectile function by leaving the neurovascular bundles and urethral sphincters intact. Accurate needle guidance is critical to the success of FLA. Multiparametric magnetic resonance images (mpMRI) can be used to identify targets, guide needles, and assess treatment outcomes. The purpose of this work was to design and evaluate the accuracy of an MR‐compatible mechatronic system for in‐bore transperineal guidance of FLA ablation needles to localized lesions in the prostate. Methods: The mechatronic system was constructed entirely of non‐ferromagnetic materials, with actuation controlled by piezoelectric motors and optical encoders. The needle guide hangs between independent front and rear two‐link arms, which allows for horizontal and vertical translation as well as pitch and yaw rotation of the guide with a 6.0 cm range of motion in each direction. Needles are inserted manually through a chosen hole in the guide, which has been aligned with the target in the prostate. Open‐air positioning error was evaluated using an optical tracking system (0.25 mm RMS accuracy) to measure 125 trajectories in free space. Correction of systematic bias in the system was performed using 85 of the trajectories, and the remaining 40 were used to estimate the residual error. The error was calculated as the horizontal and vertical displacement between the axis of the desired and measured trajectories at a typical needle insertion depth of 10 cm. MR‐compatibility was evaluated using a grid phantom to assess image degradation due to the presence of the system, and induced force, heating, and electrical interference in the system were assessed qualitatively. In‐bore positioning error was evaluated on 25 trajectories. Results: Open‐air mean positioning error at the needle tip was 0.80 ± 0.36 mm with a one‐sided 95% confidence interval of 1.40 mm. The mean deviation of needle trajectories from the planned direction was 0.14 ± 0.06∘. In the MR bore, the mean positioning error at the needle tip was 2.11 ± 1.05 mm with a one‐sided 95% prediction interval of 3.84 mm. The mean angular error was 0.49 ± 0.26∘. The system was found to be compatible with the MR environment under the specified gradient‐echo sequence parameters used in this study. Conclusion: A complete system for delivering needles to localized prostate tumors was developed and described in this work, and its compatibility with the MR environment was demonstrated. In‐bore MRI positioning error was sufficiently small for targeting small localized prostate tumors. [ABSTRACT FROM AUTHOR]

We investigate conditional specifications of the five-factor Fama-French (FF) model, augmented with traditional illiquidity measures. The motivation for this time-varying methodology is that the traditional static approach of the FF model may be misspecified, especially for the endogenous illiquidity measures. We focus on the time-varying nature of the Jensen performance measure α and the market systematic risk sensitivity β, as these parameters are essentially universal in asset pricing models. To tackle endogeneity and other specification errors, we rely on our robust instrumental variables (RIV) algorithm implemented via a GMM approach. In this dynamic or time-varying conditional context, we generally find that the most significant factor is the market one, but illiquidity may matter depending on which states or estimation methods we consider. In particular, sectors whose returns embed a market illiquidity premium are more exposed to a binding funding constraint in times of crisis, which leads to deleveraging and a resulting decrease in systematic risk. [ABSTRACT FROM AUTHOR]

Purpose: Prostate cancer is the most common noncutaneous cancer among men in the USA. Focal laser thermal ablation (FLA) has the potential to control small tumors while preserving urinary and erectile function by leaving the neurovascular bundles and urethral sphincters intact. Accurate needle guidance is critical to the success of FLA. Multiparametric magnetic resonance images (mpMRI) can be used to identify targets, guide needles, and assess treatment outcomes. In this study, we evaluated the location of ablation zones relative to targeted lesions in 23 patients who underwent FLA therapy in a phase II trial. The ablation zone margins and unablated tumor volume were measured to determine whether complete coverage of each tumor was achieved, which would be considered a clinically successful ablation. Methods: Preoperative mpMRI was acquired for each patient 2–3 months preceding the procedure and the prostate and lesion(s) were manually contoured on 3 T T2‐weighted axial images. The prostate and ablation zone(s) were also manually contoured on postablation 1.5 T T1‐weighted contrast‐enhanced axial images acquired immediately after the procedure intraoperatively. The lesion surface was nonrigidly registered to the postablation image using an initial affine registration followed by nonrigid thin‐plate spline registration of the prostate surfaces. The margins between the registered lesion and ablation zone were calculated using a uniform spherical distribution of rays, and the volume of intersection was also calculated. Each prostate was contoured five times to determine the segmentation variability and its effect on intersection of the lesion and ablation zone. Results: Our study showed that the boundaries of the segmented tumor and ablation zone were close. Of the 23 lesions that were analyzed, 11 were completely covered by the ablation zone and 12 were partially covered. A shift of 1.0, 2.0, and 2.6 mm would result in 19, 21, and all tumors completely covered by the ablation zone, respectively. The median unablated tumor volume across all tumors was 0.1 mm3 with an IQR of 3.7 mm3, which was 0.2% of the median tumor volume (46.5 mm3 with an IQR of 46.3 mm3). The median extension of the tumors beyond the ablation zone, in cases which were partially ablated, was 0.9 mm (IQR of 1.3 mm), with the furthest tumor extending 2.6 mm. Conclusion: In all cases, the boundary of the tumor was close to the boundary of the ablation zone, and in some cases, the boundary of the ablation zone did not completely enclose the tumor. Our results suggest that some of the ablations were not clinically successful and that there is a need for more accurate needle tracking and guidance methods. Limitations of the study include errors in the registration and segmentation methods used as well as different voxel sizes and contrast between the registered T2 and T1 MRI sequences and asymmetric swelling of the prostate postprocedurally. [ABSTRACT FROM AUTHOR]

This paper presents the concept of psychological point of equilibrium (PPE), which is a mental state achieved by average investors when trying to make decisions during market bubble's inflationary stages. The PPE results from an interplay between agents acting in a volatile market that is characterized by predatory behaviors. Prior to the 2008 subprime crisis, average investors are assumed to have displaced their logical PPEs in large part as a consequence of their attraction towards predatory mortgages and teaser rates. A better understanding of average investor's vulnerabilities may help governments to implement more efficient measures aimed at curving predatory behaviors. [ABSTRACT FROM PUBLISHER]

In this article, the authors develop a closed-form solution for assessing the capital investment projectNPVvariance when cash flows obey a first-order autoregressive process. A distinction is established between static and dynamic solutions as the authors focus on the case involving partial positive dependence between cash flows. Under a Markovian process, theNPVsolution is stationary in mean but not strictly in variance. Constraining the process to become fully stationary will overestimate theNPVvariance. Finally, the authors show that the MarkovianNPVvariance closed-form solution is robust to the introduction of autoregressive conditional heteroscedastic variances complying with a GARCH(1,1) process; it will, however, have its value increased and consequently the riskiness of the capital investment project. [ABSTRACT FROM PUBLISHER]

ABSTRACT This article proposes a probabilistic approach to project operational risk and project portfolio risk diversification. The analysis rests on a fundamental distinction between a fractional and an additive approach for constructing portfolios. Since the additive approach excludes variance as a measure of risk, the project's operational risk is defined by its probability of loss. Paradoxically, the effectiveness of any firm's portfolio risk diversification process will be negatively related to the operational risk of its representative project. We also present the conditions under which risk management and efficiency management can contribute to the firm's strategic imperative of lowering its operational risk. [ABSTRACT FROM AUTHOR]

Purpose: Prostate segmentation is an important step in the planning and treatment of 3D end-firing transrectal ultrasound (TRUS) guided prostate biopsy. In order to improve the accuracy and efficiency of prostate segmentation in 3D TRUS images, an improved level set method is incorporated into a rotational-slice-based 3D prostate segmentation to decrease the accumulated segmentation errors produced by the slice-by-slice segmentation method. Methods: A 3D image is first resliced into 2D slices in a rotational manner in both the clockwise and counterclockwise directions. All slices intersect approximately along the rotational scanning axis and have an equal angular spacing. Six to eight boundary points are selected to initialize a level set function to extract the prostate contour within the first slice. The segmented contour is then propagated to the adjacent slice and is used as the initial contour for segmentation. This process is repeated until all slices are segmented. A modified distance regularization level set method is used to segment the prostate in all resliced 2D slices. In addition, shape-constraint and local-region-based energies are imposed to discourage the evolved level set function to leak in regions with weak edges or without edges. An anchor point based energy is used to promote the level set function to pass through the initial selected boundary points. The algorithm's performance was evaluated using distance- and volume-based metrics (sensitivity (Se), Dice similarity coefficient (DSC), mean absolute surface distance (MAD), maximum absolute surface distance (MAXD), and volume difference) by comparison with expert delineations. Results: The validation results using thirty 3D patient images showed that the authors' method can obtain a DSC of 93.1% ± 1.6%, a sensitivity of 93.0% ± 2.0%, a MAD of 1.18 ± 0.36 mm, a MAXD of 3.44 ± 0.8 mm, and a volume difference of 2.6 ± 1.9 cm3 for the entire prostate. A reproducibility experiment demonstrated that the proposed method yielded low intraobserver and interobserver variability in terms of DSC. The mean segmentation time of the authors' method for all patient 3D TRUS images was 55 ± 3.5 s, in addition to 30 ± 5 s for initialization. Conclusions: To address the challenges involved with slice-based 3D prostate segmentation, a level set based method is proposed in this paper. This method is especially developed for a 3D end-firing TRUS guided prostate biopsy system. The extensive experimental results demonstrate that the proposed method is accurate, robust, and computationally efficient. [ABSTRACT FROM AUTHOR]

Purpose: Prostate adenocarcinoma is the most common noncutaneous malignancy in American men with over 200 000 new cases diagnosed each year. Prostate interventional therapy, such as cryotherapy and brachytherapy, is an effective treatment for prostate cancer. Its success relies on the correct needle implant position. This paper proposes a robust and efficient needle segmentation method, which acts as an aid to localize the needle in three-dimensional (3D) transrectal ultrasound (TRUS) guided prostate therapy. Methods: The procedure of locating the needle in a 3D TRUS image is a three-step process. First, the original 3D ultrasound image containing a needle is cropped; the cropped image is then converted to a binary format based on its histogram. Second, a 3D Hough transform based needle segmentation method is applied to the 3D binary image in order to locate the needle axis. The position of the needle endpoint is finally determined by an optimal threshold based analysis of the intensity probability distribution. The overall efficiency is improved through implementing a coarse-fine searching strategy. The proposed method was validated in tissue-mimicking agar phantoms, chicken breast phantoms, and 3D TRUS patient images from prostate brachytherapy and cryotherapy procedures by comparison to the manual segmentation. The robustness of the proposed approach was tested by means of varying parameters such as needle insertion angle, needle insertion length, binarization threshold level, and cropping size. Results: The validation results indicate that the proposed Hough transform based method is accurate and robust, with an achieved endpoint localization accuracy of 0.5 mm for agar phantom images, 0.7 mm for chicken breast phantom images, and 1 mm for in vivo patient cryotherapy and brachytherapy images. The mean execution time of needle segmentation algorithm was 2 s for a 3D TRUS image with size of 264 × 376 × 630 voxels. Conclusions: The proposed needle segmentation algorithm is accurate, robust, and suitable for 3D TRUS guided prostate transperineal therapy. [ABSTRACT FROM AUTHOR]

Introduction: This study evaluates the clinical benefit of magnetic resonance-transrectal ultrasound (MR-TRUS) fusion biopsy over systematic biopsy between first-time and repeat prostate biopsy patients with prior atypical small acinar proliferation (ASAP). Materials: 100 patients were enrolled in a single-centre prospective cohort study: 50 for first biopsy, 50 for repeat biopsy with prior ASAP. Multiparameteric magnetic resonance imaging (MP-MRI) and standard 12-core ultrasound biopsy (Std-Bx) were performed on all patients. Targeted biopsy using MRI-TRUS fusion (Fn-Bx) was performed f suspicious lesions were identified on the prebiopsy MP-MRI. Classification of clinically significant disease was assessed independently for the Std-Bx vs. Fn-Bx cores to compare the two approaches. Results: Adenocarcinoma was detected in 49/100 patients (26 first biopsy, 23 ASAP biopsy), with 25 having significant disease (17 first, 8 ASAP). Fn-Bx demonstrated significantly higher per-core cancer detection rates, cancer involvement, and Gleason scores for first-time and ASAP patients. However, Fn-Bx was significantly more likely to detect significant cancer missed on Std-Bx for ASAP patients than first-time biopsy patients. The addition of Fn-Bx to Std-Bx for ASAP patients had a 166.7% relative risk reduction for missing Gleason a 3 + 4 disease (number needed to image with MP-MRI=10 patients) compared to 6.3% for first biopsy (number to image=50 patients). Negative predictive value of MP-MRI for negative biopsy was 79% for first-time and 100% for ASAP patients, with median followup of 32.1 ± 15.5 months. Conclusions: MR-TRUS Fn-Bx has a greater clinical impact for repeat biopsy patients with prior ASAP than biopsy-naïve patients by detecting more significant cancers that are missed on Std-Bx. [ABSTRACT FROM AUTHOR]

Objective. Ultrasound is the most commonly used examination for the detection and identification of thyroid nodules. Since manual detection is time-consuming and subjective, attempts to introduce machine learning into this process are ongoing. However, the performance of these methods is limited by the low signal-to-noise ratio and tissue contrast of ultrasound images. To address these challenges, we extend thyroid nodule detection from image-based to video-based using the temporal context information in ultrasound videos. Approach. We propose a video-based deep learning model with adjacent frame perception (AFP) for accurate and real-time thyroid nodule detection. Compared to image-based methods, AFP can aggregate semantically similar contextual features in the video. Furthermore, considering the cost of medical image annotation for video-based models, a patch scale self-supervised model (PASS) is proposed. PASS is trained on unlabeled datasets to improve the performance of the AFP model without additional labelling costs. Main results. The PASS model is trained by 92 videos containing 23 773 frames, of which 60 annotated videos containing 16 694 frames were used to train and evaluate the AFP model. The evaluation is performed from the video, frame, nodule, and localization perspectives. In the evaluation of the localization perspective, we used the average precision metric with the intersection-over-union threshold set to 50% (AP@50), which is the area under the smoothed Precision-Recall curve. Our proposed AFP improved AP@50 from 0.256 to 0.390, while the PASS-enhanced AFP further improved the AP@50 to 0.425. AFP and PASS also improve the performance in the valuations of other perspectives based on the localization results. Significance. Our video-based model can mitigate the effects of low signal-to-noise ratio and tissue contrast in ultrasound images and enable the accurate detection of thyroid nodules in real-time. The evaluation from multiple perspectives of the ablation experiments demonstrates the effectiveness of our proposed AFP and PASS models., (© 2023 Institute of Physics and Engineering in Medicine.)

In this paper, we propose a novel global optimization based 3-D multi-region segmentation algorithm for T1-weighted black-blood carotid magnetic resonance (MR) images. The proposed algorithm partitions a 3-D carotid MR image into three regions: wall, lumen, and background. The algorithm performs such partitioning by simultaneously evolving two coupled 3-D surfaces of carotid artery adventitia boundary (AB) and lumen-intima boundary (LIB) while preserving their anatomical inter-surface consistency such that the LIB is always located within the AB. In particular, we show that the proposed algorithm results in a fully time implicit scheme that propagates the two linearly ordered surfaces of the AB and LIB to their globally optimal positions during each discrete time frame by convex relaxation. In this regard, we introduce the continuous max-flow model and prove its duality/equivalence to the convex relaxed optimization problem with respect to each evolution step. We then propose a fully parallelized continuous max-flow-based algorithm, which can be readily implemented on a GPU to achieve high computational efficiency. Extensive experiments, with four users using 12 3T MR and 26 1.5T MR images, demonstrate that the proposed algorithm yields high accuracy and low operator variability in computing vessel wall volume. In addition, we show the algorithm outperforms previous methods in terms of high computational efficiency and robustness with fewer user interactions.

Prostate segmentation in 3D ultrasound images is an important step in the planning and treatment of 3D end-firing transrectal ultrasound (TRUS) guided prostate biopsy. A semi-automatic prostate segmentation method is presented in this paper, which integrates a modified distance regularization level set formulation with shape constraint to a rotational-slice-based 3D prostate segmentation method. Its performance, using different metrics, has been evaluated on a set of twenty 3D patient prostate images by comparison with expert delineations. The volume overlap ratio of 93.39 +/- 1.26% and the mean absolute surface distance of 1.16 +/- 0.34 mm were found in the quantitative validation result.