Latest AI and machine learning research in radiology for healthcare professionals.
BACKGROUND: The angiography-derived non-hyperemic pressure ratio (angioNHPR) is a novel index of NHP...
Cancer, a global health threat, demands effective diagnostic solutions to combat its impact on publi...
Multi-modality imaging is widely used in clinical practice and biomedical research to gain a compreh...
Recently, Deep Learning (DL) models have shown promising accuracy in analysis of medical images. Alz...
The early detection of Alzheimer's Disease (AD) is thought to be important for effective interventio...
The integration of Digital Breast Tomosynthesis (DBT) and Artificial Intelligence (AI) represents a ...
OBJECTIVE: Early and accurate prediction of axillary lymph node metastasis (ALNM) is crucial in dete...
BACKGROUND: In magnetic resonance image (MRI)-guided radiotherapy (MRgRT), 2D rapid imaging is commo...
The COVID-19 pandemic has emerged as a global health crisis, impacting millions worldwide. Although ...
The latest developments combining deep learning technology and medical image data have attracted wid...
PURPOSE: This study aimed to investigate the performance of multiparametric magnetic resonance imagi...
The utilization of artificial intelligence (AI) is expanding significantly within medical research a...
Large language models (LLMs) and multi-modal large language models (MLLMs) represent the cutting-edg...
PURPOSE: The objective of this study is to generate reliable K parametric images from a shortened [F...
Magnetic resonance imaging (MRI) of the knee is the recommended diagnostic method before invasive ar...
OBJECTIVE: To explore the performance of deep learning-based segmentation of infarcted lesions in th...
BACKGROUND/INTRODUCTION: To evaluate the performance of pre-trained deep learning schemes (DLS) in h...
Portable, low-field magnetic resonance imaging (LF-MRI) of the brain may facilitate point-of-care as...
PURPOSE: Coronary CT angiography (CCTA) is well established for the diagnostic evaluation and progno...
OBJECTIVES: To assess the current state-of-the-art in deep learning methods applied to pre-operative...
Medical image analysis poses significant challenges due to limited availability of clinical data, wh...