Rectal cancer (RC) accounts for approximately one‐third of colorectal cancer (CRC), with
death rates increasing in patients younger than 50 years old. Magnetic resonance imaging …

This review provides an overview of the application of artificial intelligence (AI) in radiation
therapy (RT) from a radiation oncologist's perspective. Over the years, advances in …

Objectives To investigate the feasibility and efficacy of a deep-learning (DL)-based three-
dimensional (3D) super-resolution (SR) MRI radiomics model for preoperative T-staging …

Radiomics is an advanced image-processing framework, which extracts image features and
considers them as biomarkers towards personalized medicine. Applications include disease …

Simple Summary This study developed CT-based radiomics signatures using the least
absolute shrinkage and selection operator (LASSO), random forest (RF) and support vector …

Rectal cancer (RC) is one of the most common tumours worldwide in both males and
females, with significant morbidity and mortality rates, and it accounts for approximately one …

Purpose To investigate the reproducibility of radiomics features extracted from two-
dimensional regions of interest (2D ROIs) versus whole lung (3D) ROIs in repeated in-vivo …

Rationale and Objectives The 15%-27% of patients with locally advanced rectal cancer
(LARC) achieved pathologic complete response (pCR) to neoadjuvant chemoradiotherapy …

Background Traditional biopsies pose risks and may not accurately reflect soft tissue
sarcoma (STS) heterogeneity. MRI provides a noninvasive, comprehensive alternative …

(1) Background: An increasing amount of research has supported the role of radiomics for
predicting pathological complete response (pCR) to neoadjuvant chemoradiation treatment …