OBJECTIVE. The purpose of this study is to retrospectively investigate whether pretreatment
multiparametric MRI findings can predict biochemical recurrence in patients who underwent …

In this work, we present a new methodology to facilitate prediction of recurrent prostate
cancer (CaP) following radical prostatectomy (RP) via the integration of quantitative image …

Currently the diagnosis of local recurrence of prostate cancer (PCa) after radical
prostatectomy (RT) is based on the onset of biochemical failure which is defined by two …

We aimed to study radiomics approach based on biparametric magnetic resonance imaging
(MRI) for determining significant residual cancer after androgen deprivation therapy (ADT) …

Purpose Focal salvage treatments of recurrent prostate cancer (PCa) after radiation therapy
require accurate delineation of the target volume. Magnetic resonance imaging (MRI) is …

This study aimed to develop a noninvasive Machine Learning (ML) model to identify
clinically significant prostate cancer (csPCa) according to Gleason Score (GS) based on …

Purpose To establish machine learning (ML) models for the diagnosis of clinically significant
prostate cancer (csPC) using multiparameter magnetic resonance imaging (mpMRI), texture …

Objectives To develop radiomics models based on automatic segmentation of the
pretreatment apparent diffusion coefficient (ADC) maps for predicting the biochemical …

The use of quantitative radiomic features of MRI to predict the aggressiveness of prostate
cancer has attracted increasing amounts of attention due to its potential as anon-invasive …

The development of precise medical imaging has facilitated the establishment of radiomics,
a computer-based method of quantitatively analyzing subvisual imaging characteristics. The …