Advances in quantitative biomarker development have accelerated new forms of data-driven
insights for patients with cancer. However, most approaches are limited to a single mode of …

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 …

We present a multi-stage 3D computer-aided detection and diagnosis (CAD) model 1 for
automated localization of clinically significant prostate cancer (csPCa) in bi-parametric MR …

Purpose To evaluate a novel method of semisupervised learning (SSL) guided by
automated sparse information from diagnostic reports to leverage additional data for deep …

Automated methods for detecting prostate cancer and distinguishing indolent from
aggressive disease on Magnetic Resonance Imaging (MRI) could assist in early diagnosis …

Magnetic resonance imaging (MRI) is an increasingly important tool for the diagnosis and
treatment of prostate cancer. However, interpretation of MRI suffers from high inter-observer …

Image processing technology has always been a hot and difficult topic in the field of artificial
intelligence. With the rise and development of machine learning and deep learning …

Purpose While multi‐parametric magnetic resonance imaging (MRI) shows great promise in
assisting with prostate cancer diagnosis and localization, subtle differences in appearance …

Nowadays, deep learning methods with large-scale datasets can produce clinically useful
models for computer-aided diagnosis. However, the privacy and ethical concerns are …

The use of MRI for prostate cancer diagnosis and treatment is increasing rapidly. However,
identifying the presence and extent of cancer on MRI remains challenging, leading to high …