AIMC Topic: Prostate

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Development and clinical implementation of SeedNet: A sliding-window convolutional neural network for radioactive seed identification in MRI-assisted radiosurgery (MARS).

Magnetic resonance in medicine Feb 8, 2019
PURPOSE: To develop and evaluate a sliding-window convolutional neural network (CNN) for radioactive seed identification in MRI of the prostate after permanent implant brachytherapy.
Algorithms Retrospective Studies Male Humans Neural Networks, Computer Brachytherapy Radiosurgery Magnetic Resonance Imaging, Interventional Image Processing, Computer-Assisted Prostatic Neoplasms Prostate
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Detection of Extraprostatic Extension of Cancer on Biparametric MRI Combining Texture Analysis and Machine Learning: Preliminary Results.

Academic radiology Jan 14, 2019
RATIONALE AND OBJECTIVES: Extraprostatic extension of disease (EPE) has a major role in risk stratification of prostate cancer patients. Currently, pretreatment local staging is performed with MRI, while the gold standard is represented by histopatho...
Humans Machine Learning Algorithms Prostatectomy Neoplasm Invasiveness Predictive Value of Tests Bayes Theorem Prostatic Neoplasms Neoplasm Staging Prostate Prognosis Middle Aged Aged Risk Assessment Male Magnetic Resonance Imaging
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A propagation-DNN: Deep combination learning of multi-level features for MR prostate segmentation.

Computer methods and programs in biomedicine Dec 29, 2018
BACKGROUND AND OBJECTIVE: Prostate segmentation on Magnetic Resonance (MR) imaging is problematic because disease changes the shape and boundaries of the gland and it can be difficult to separate the prostate from surrounding tissues. We propose an a...
Neural Networks, Computer Algorithms Male Humans Deep Learning Magnetic Resonance Imaging Prostate
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Learning deep similarity metric for 3D MR-TRUS image registration.

International journal of computer assisted radiology and surgery Oct 31, 2018
PURPOSE: The fusion of transrectal ultrasound (TRUS) and magnetic resonance (MR) images for guiding targeted prostate biopsy has significantly improved the biopsy yield of aggressive cancers. A key component of MR-TRUS fusion is image registration. H...
Male Deep Learning Ultrasonography Imaging, Three-Dimensional Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Neural Networks, Computer Phantoms, Imaging Prostatic Neoplasms Prostate Biopsy
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Predicting Advanced Prostate Cancer from Modeling Early Indications in Biopsy and Prostatectomy Samples via Transductive Semi-Supervised Survival Analysis.

BioMed research international Oct 21, 2018
Prostate cancer is the most prevalent form of cancer and the second most common cause of cancer deaths among men in the United States. Accurate prognosis is important as it is the principal factor in determining the treatment plan. Prostate cancer is...
Prostate Biopsy Supervised Machine Learning Prostatectomy Humans Male Algorithms Regression Analysis Prostatic Neoplasms
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Automatic Needle Segmentation and Localization in MRI With 3-D Convolutional Neural Networks: Application to MRI-Targeted Prostate Biopsy.

IEEE transactions on medical imaging Oct 18, 2018
Image guidance improves tissue sampling during biopsy by allowing the physician to visualize the tip and trajectory of the biopsy needle relative to the target in MRI, CT, ultrasound, or other relevant imagery. This paper reports a system for fast au...
Algorithms Male Magnetic Resonance Imaging Prostatic Neoplasms Prostate Image-Guided Biopsy Humans Neural Networks, Computer
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Path R-CNN for Prostate Cancer Diagnosis and Gleason Grading of Histological Images.

IEEE transactions on medical imaging Oct 12, 2018
Prostate cancer is the most common and second most deadly form of cancer in men in the United States. The classification of prostate cancers based on Gleason grading using histological images is important in risk assessment and treatment planning for...
Image Interpretation, Computer-Assisted Histocytochemistry Prostatic Neoplasms Neoplasm Grading Prostate Humans Neural Networks, Computer Male
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Editorial Comment to Predictors of biochemical recurrence after Retzius-sparing robot-assisted radical prostatectomy: Analysis of 359 cases with a median follow-up period of 26 months.

International journal of urology : official journal of the Japanese Urological Association Oct 12, 2018
Prostate Prostatectomy Humans Male Follow-Up Studies Robotics
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Feasibility of anatomical feature points for the estimation of prostate locations in the Bayesian delineation frameworks for prostate cancer radiotherapy.

Radiological physics and technology Sep 28, 2018
This study aimed to investigate the feasibility of anatomical feature points for the estimation of prostate locations in the Bayesian delineation frameworks for prostate cancer radiotherapy. The relationships between the reference centroids of prosta...
Prostatic Neoplasms Prostate Feasibility Studies Humans Tomography, X-Ray Computed Radiotherapy Planning, Computer-Assisted Machine Learning Male Bayes Theorem
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An EM-based semi-supervised deep learning approach for semantic segmentation of histopathological images from radical prostatectomies.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Sep 3, 2018
Automated Gleason grading is an important preliminary step for quantitative histopathological feature extraction. Different from the traditional task of classifying small pre-selected homogeneous regions, semantic segmentation provides pixel-wise Gle...
Male Prostatectomy Deep Learning Prostatic Neoplasms Image Processing, Computer-Assisted Prostate Humans Supervised Machine Learning Algorithms
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