Latest AI and machine learning research in radiology for healthcare professionals.
PURPOSE: To develop a deep learning-based framework for automated detection and grading of breast ar...
PURPOSE: To compare biparametric MRI (bpMRI) and multiparametric MRI (mpMRI) for detecting clinicall...
BACKGROUND: Quality control (QC) in echocardiography is crucial but is often subjective, retrospecti...
Ultrasound image segmentation plays an important role in clinical diagnosis, but existing deep learn...
The proposed multi-modal deep learning system for lung cancer diagnosis and characterisation uses st...
Accurate extraction of the left ventricular (LV)-centred region of interest (ROI) in stress perfusio...
In major grain-producing regions, hydrothermal processes are critical for regulating ecosystem stabi...
Artificial intelligence (AI) is transforming veterinary diagnostic imaging, improving the accuracy, ...
INTRODUCTION: Gastric intestinal metaplasia (GIM) and gastric dysplasia are critical precursors in t...
RATIONALE AND OBJECTIVE: Anaplastic thyroid carcinoma (ATC) may arise from the progression of differ...
OBJECTIVE: To investigate whether the 48-month change in effusion-synovitis volume (ΔESV) is associa...
Prostate magnetic resonance imaging (MRI) is central to the detection and localization of clinically...
Deep learning (DL) image analysis of prostate MRI can be integrated into the prostate cancer diagnos...
PURPOSE: The purpose of this study was to develop an artificial intelligence (AI) tool to assist rec...
Magnetic Resonance Imaging (MRI) is a non-invasive imaging method that can give detailed visualizati...
Early and accurate detection of brain tumors is clinically valuable for improving prognosis and guid...
OBJECTIVES: The need for a cost-effective, rapid, and increasingly accessible alternative to the 21-...
BACKGROUND: Mucosal thickness (MT) is a key factor influencing peri-implant soft-tissue response and...
The Ovarian-Adnexal Reporting and Data System (O-RADS), developed by the American College of Radiolo...
PURPOSE: To develop and rigorously evaluate a hyperparameter-optimized custom convolutional neural n...
PURPOSE: To develop a dual-contrast deep-learning model for automated muscle segmentation on spin-ec...