Computer-extracted tumour characteristics have been incorporated into medical imaging
computer-aided diagnosis (CAD) algorithms for decades. With the advent of radiomics, an …

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 …

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

We hypothesized that state-of-the-art AI models, trained using thousands of patient cases,
are non-inferior to radiologists at clinically significant prostate cancer diagnosis using MRI …

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

Prostate cancer, the most common cancer in men, is influenced by age, family history,
genetics, and lifestyle factors. Early detection of prostate cancer using screening methods …

Artificial intelligence (AI) for prostate magnetic resonance imaging (MRI) is starting to play a
clinical role for prostate cancer (PCa) patients. AI-assisted reading is feasible, allowing …

Background Using visual, biological, and electronic health records data as the sole input
source, pretrained convolutional neural networks and conventional machine learning …

Introduction to BiomedicalImaging A state-of-the-art exploration of the foundations and latest
developments in biomedical imaging technology In the newly revised second edition of …

Multiparametric magnetic resonance imaging (mpMRI) is an indispensable tool in the
clinical workflow for the diagnosis and treatment planning of various diseases. Machine …