AIMC Topic: Prostatic Neoplasms

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Synthetic MRI-aided multi-organ segmentation on male pelvic CT using cycle consistent deep attention network.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Manual contouring is labor intensive, and subject to variations in operator knowledge, experience and technique. This work aims to develop an automated computed tomography (CT) multi-organ segmentation method for prostate canc...

Classification of Cancer at Prostate MRI: Deep Learning versus Clinical PI-RADS Assessment.

Radiology
Background Men suspected of having clinically significant prostate cancer (sPC) increasingly undergo prostate MRI. The potential of deep learning to provide diagnostic support for human interpretation requires further evaluation. Purpose To compare t...

Optimizing robot motion for robotic ultrasound-guided radiation therapy.

Physics in medicine and biology
An important aspect of robotic radiation therapy is active compensation of target motion. Recently, ultrasound has been proposed to obtain real-time volumetric images of abdominal organ motion. One approach to realize flexible probe placement through...

Effect of bladder neck sparing at robot-assisted laparoscopic prostatectomy on postoperative continence rates and biochemical recurrence.

Urologic oncology
OBJECTIVES: Previous studies reported improved continence recovery by bladder neck sparing (BNS) in prostate cancer patients treated with robot-assisted laparoscopic radical prostatectomy (RALP), without compromising biochemical recurrence (BCR). We ...

Semi-supervised mp-MRI data synthesis with StitchLayer and auxiliary distance maximization.

Medical image analysis
The availability of a large amount of annotated data is critical for many medical image analysis applications, in particular for those relying on deep learning methods which are known to be data-hungry. However, annotated medical data, especially mul...

Deep Learning-Based Gleason Grading of Prostate Cancer From Histopathology Images-Role of Multiscale Decision Aggregation and Data Augmentation.

IEEE journal of biomedical and health informatics
Visual inspection of histopathology images of stained biopsy tissue by expert pathologists is the standard method for grading of prostate cancer (PCa). However, this process is time-consuming and subject to high inter-observer variability. Machine le...

Automatic segmentation of prostate MRI using convolutional neural networks: Investigating the impact of network architecture on the accuracy of volume measurement and MRI-ultrasound registration.

Medical image analysis
Convolutional neural networks (CNNs) have recently led to significant advances in automatic segmentations of anatomical structures in medical images, and a wide variety of network architectures are now available to the research community. For applica...