World-wide incidence rate of prostate cancer has progressively increased with time
especially with the increased proportion of elderly population. Early detection of prostate …

Abstract “Radiomics,” as it refers to the extraction and analysis of a large number of
advanced quantitative radiological features from medical images using high-throughput …

Background The development of deep learning (DL) models for prostate segmentation on
magnetic resonance imaging (MRI) depends on expert-annotated data and reliable …

The recent developments in deep learning techniques evolved to new heights in various
domains and applications. The recognition, translation, and video generation of Sign …

Background Due to the large variability in the prostate gland of different patient groups,
manual segmentation is time-consuming and subject to inter-and intra-reader variations …

Medical image segmentation under federated learning (FL) is a promising direction by
allowing multiple clinical sites to collaboratively learn a global model without centralizing …

Abstract Introduction Primary prostate cancer (PCa) can be visualized on prostate-specific
membrane antigen positron emission tomography (PSMA-PET) with high accuracy …

Purpose To develop a deep learning model to delineate the transition zone (TZ) and
peripheral zone (PZ) of the prostate on MR images. Materials and Methods This …

Background The potential of deep learning to support radiologist prostate magnetic
resonance imaging (MRI) interpretation has been demonstrated. Purpose The aim of this …

Purpose To assess the clinical acceptability of a commercial deep-learning-based auto-
segmentation (DLAS) prostate model that was retrained using institutional data for …