Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male
population. The diagnosis, the identification of aggressive disease, and the post-treatment …

Radiomics and genomics represent two of the most promising fields of cancer research,
designed to improve the risk stratification and disease management of patients with prostate …

In this study we assessed the repeatability of radiomics features on small prostate tumors
using test-retest Multiparametric Magnetic Resonance Imaging (mpMRI). The premise of …

Due to the upfront role of magnetic resonance imaging (MRI) for prostate cancer (PCa)
diagnosis, a multitude of artificial intelligence (AI) applications have been suggested to aid …

Background A definitive diagnosis of prostate cancer requires a biopsy to obtain tissue for
pathologic analysis, but this is an invasive procedure and is associated with complications …

Objectives We systematically reviewed the current literature evaluating the ability of fully-
automated deep learning (DL) and semi-automated traditional machine learning (TML) MRI …

Prostate cancer (PCa) is one of the most frequently diagnosed malignancies of men in the
world. Due to a variety of treatment options in different risk groups, proper diagnostic and …

A multitude of studies have explored the role of artificial intelligence (AI) in providing
diagnostic support to radiologists, pathologists, and urologists in prostate cancer detection …

The role of multiparametric MRI (mpMRI) in the detection of prostate cancer is well-
established. Based on the limited role of dynamic contrast enhancement (DCE) in PI-RADS …

Significant prostate carcinoma (sPCa) classification based on MRI using radiomics or deep
learning approaches has gained much interest, due to the potential application in assisting …