In the present work, we present a publicly available, expert-segmented representative
dataset of 158 3.0 Tesla biparametric MRIs [1]. There is an increasing number of studies …

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

Simple Summary Prostate cancer represents a highly prevalent form of cancer worldwide,
with timely detection and treatment being crucial for achieving a high survival rate. Manual …

Background. Prostate segmentation is a crucial step in computer-aided systems for prostate
cancer detection. Multi-planar acquisitions are commonly used by clinicians to obtain a more …

Multiparametric (mp) magnetic resonance imaging (MRI) represents a robust tool for
detecting prostate cancers (PCa). However, its interpretation requires skilled and …

Please see the Author Video associated with this article. OBJECTIVE. Prostate cancer is the
most commonly diagnosed cancer in men in the United States with more than 200,000 new …

Objective Automatic MR imaging segmentation of the prostate provides relevant clinical
benefits for prostate cancer evaluation such as calculation of automated PSA density and …

Prostate cancer (PCa) is a severe disease among men globally. It is important to identify
PCa early and make a precise diagnosis for effective treatment. For PCa diagnosis, Multi …

Background Accurate whole prostate segmentation on magnetic resonance imaging (MRI) is
important in the management of prostatic diseases. In this multicenter study, we aimed to …

Objective Automated methods for prostate segmentation on MRI are typically developed
under ideal scanning and anatomical conditions. This study evaluates three different …