BACKGROUND: The advantages of Robot-assisted laparoscopic prostatectomy (RARP) over open radical prostatectomy (ORP) in Prostate cancer perioperatively are well-established, but quality of life is more contentious. Increasingly, patients are utilisin...
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...
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Aug 30, 2018
Whole-body attenuation correction (AC) is still challenging in combined PET/MR scanners. We describe Dixon-VIBE Deep Learning (DIVIDE), a deep-learning network that allows synthesizing pelvis pseudo-CT maps based only on the standard Dixon volumetric...
Accurate segmentation of pelvic organs (i.e., prostate, bladder, and rectum) from CT image is crucial for effective prostate cancer radiotherapy. However, it is a challenging task due to: 1) low soft tissue contrast in CT images and 2) large shape an...
The quality of radiotherapy has greatly improved due to the high precision achieved by intensity-modulated radiation therapy (IMRT). Studies have been conducted to increase the quality of planning and reduce the costs associated with planning through...
The Gleason grading system remains the most powerful prognostic predictor for patients with prostate cancer since the 1960s. Its application requires highly-trained pathologists, is tedious and yet suffers from limited inter-pathologist reproducibili...
International journal of radiation oncology, biology, physics
Aug 6, 2018
PURPOSE: This study was designed to apply artificial neural network (ANN) classification methods for the prediction of late fecal incontinence (LFI) after high-dose prostate cancer radiation therapy and to develop a ready-to-use graphical tool.
OBJECTIVES: To train and compare machine-learning algorithms with traditional regression analysis for the prediction of early biochemical recurrence after robot-assisted prostatectomy.
Purpose To compare biparametric contrast-free radiomic machine learning (RML), mean apparent diffusion coefficient (ADC), and radiologist assessment for characterization of prostate lesions detected during prospective MRI interpretation. Materials an...
One of the fundamental challenges in supervised learning for multimodal image registration is the lack of ground-truth for voxel-level spatial correspondence. This work describes a method to infer voxel-level transformation from higher-level correspo...