Simple Summary The primary purpose of this review is to provide an in-depth analysis of
existing Artificial Intelligence (AI) algorithms used in the field of prostate cancer (PC) for …

Purpose Prediction of extraprostatic extension (EPE) is essential for accurate surgical
planning in prostate cancer (PCa). Radiomics based on magnetic resonance imaging (MRI) …

Image registration can map the ground truth extent of prostate cancer from histopathology
images onto MRI, facilitating the development of machine learning methods for early …

Objectives Extraprostatic extension (EPE) of prostate cancer (PCa) is predicted using clinical
nomograms. Incorporating MRI could represent a leap forward, although poor sensitivity and …

Objectives To evaluate the added benefit of integrating features from pre-treatment MRI
(radiomics) and digitized post-surgical pathology slides (pathomics) in prostate cancer …

The enlargement of the prostate gland in the reproductive system of males is considered a
form of prostate cancer (PrC). The survival rate is considerably improved with earlier …

Rationale and Objectives Extraprostatic extension (EPE) is well established as a significant
predictor of prostate cancer aggression and recurrence. Accurate EPE assessment prior to …

Magnetic resonance (MR) images require a process known as windowing for optimizing the
display conditions. However, the conventional windowing process often fails to achieve the …

Extracapsular extension (ECE) is detected in approximately one-third of newly diagnosed
prostate cancer (PCa) cases at stage T3a or higher and is associated with increased rates of …

Identifying indolent and aggressive prostate cancers is a critical problem for optimal
treatment. The existing approaches of prostate cancer detection are facing challenges as the …