Latest AI and machine learning research in radiology for healthcare professionals.
BACKGROUND: Anterior cruciate ligament (ACL) injuries may lead to long-term neuromuscular and structural adaptations in thigh muscles. Although quadriceps dysfunction is well reported, chronic changes in other muscle groups, especially in nonoperatively managed ACL-deficient individuals, remain poorly understood. METHODS: The present cohort study utilized Osteoarthritis Initiative data to assess l...
Cancer nanomedicine has evolved from the 1995 landmark approval of Doxil® into a programmable platform of precision oncology. The field now progresses along a coherent continuum that begins with passive enhanced permeability and retention (EPR)-mediated tumor accumulation, advances to active ligand-receptor targeting, and culminates in stimuli-responsive carriers whose cargo is liberated only when...
Right ventricular myocardial infarction (RVMI) is associated with higher in-hospital morbidity and mortality. Cardiac magnetic resonance (CMR) imaging...
BACKGROUND: The goals of this study were to develop an artificial intelligence (AI)-driven automated preoperative planning system for anterior cruciat...
OBJECTIVE: The purpose of this study was to develop a lightweight multimodal deep learning model for accurately predicting the risk of postoperative v...
PURPOSE: To evaluate the image quality of three reconstruction methods-filtered back projection (FBP), adaptive statistical iterative reconstruction (...
Accurate prediction of IDH mutation status in gliomas is critical for guiding diagnosis, prognosis, and treatment planning. We enrolled 2,537 preopera...
BACKGROUND: This study aimed to develop and validate deep learning (DL) models based on multiparametric MRI (mpMRI) and [18F]PSMA-1007 PET/CT to predi...
OBJECTIVES: To compare machine learning models using different combinations of clinical and imaging variables for classifying ischemic stroke patients...
OBJECTIVE: The goal of this study was to curate a prostate MRI dataset from a screening population and to train and evaluate a deep-learning segmentat...
OBJECTIVE: Diagnostic reference levels (DRLs) are essential for optimizing radiation dose in CT examinations. However, current DRLs may not reflect th...
PURPOSE: To develop accelerated 3D phase contrast (PC) MRI using jointly learned wave encoding and reconstruction. METHODS: Pseudo-fully sampled neuro...
BACKGROUND: Few studies have developed artificial intelligence (AI) systems for the automatic recognition of the anatomy of the stomach, a dynamic org...
The authentication of vegetable oils is essential for consumer protection and regulatory compliance. This study compares low-field (LF, 100 MHz) and h...
Early detection of anomalies in medical images such as brain magnetic resonance imaging (MRI) is highly relevant for diagnosis and treatment of many m...
The management of inflammatory bowel disease (IBD) relies on accurate disease assessment and close monitoring to guide therapy and evaluate treatment ...
PURPOSE: This study aims to explore the feasibility of MRI-based habitat and peritumoral radiomics for predicting the proliferative activity of stroma...
Magnetic resonance fingerprinting (MRF) enables quantitative MRI by allowing the simultaneous mapping of multiple tissue properties through innovative...
INTRODUCTION: This study integrated structural magnetic resonance imaging (sMRI) of the brain with clinical characteristics to identify the "vulnerabl...
How do humans understand the meaning of individual words? How do we combine the meaning of multiple words to comprehend novel sentences? Cognitive neu...