Radiology

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Automatic segmentation of MRI images for brain radiotherapy planning using deep ensemble learning.

This study aimed to develop and evaluate an efficient method to automatically segment T1- and T2-wei...

Clinical feasibility of deep learning-driven magnetic resonance angiography collateral map in acute anterior circulation ischemic stroke.

To validate the clinical feasibility of deep learning-driven magnetic resonance angiography (DL-driv...

Improving quantification accuracy of a nuclear Overhauser enhancement signal at -1.6 ppm at 4.7 T using a machine learning approach.

A new nuclear Overhauser enhancement (NOE)-mediated saturation transfer MRI signal at -1.6 ppm, pote...

Enhanced AMD detection in OCT images using GLCM texture features with Machine Learning and CNN methods.

Global blindness is substantially influenced by age-related macular degeneration (AMD). It significa...

Illuminating the unseen: Advancing MRI domain generalization through causality.

Deep learning methods have shown promise in accelerated MRI reconstruction but face significant chal...

Adapting to evolving MRI data: A transfer learning approach for Alzheimer's disease prediction.

Integrating 3D magnetic resonance imaging (MRI) with machine learning has shown promising results in...

Predicting Paediatric Brain Disorders from MRI Images Using Advanced Deep Learning Techniques.

The problem at hand is the significant global health challenge posed by children's diseases, where t...

Performance Evaluation and Implications of Large Language Models in Radiology Board Exams: Prospective Comparative Analysis.

BACKGROUND: Artificial intelligence advancements have enabled large language models to significantly...

Design of a Cost-Effective Ultrasound Force Sensor and Force Control System for Robotic Extra-Body Ultrasound Imaging.

Ultrasound imaging is widely valued for its safety, non-invasiveness, and real-time capabilities but...

Clinical validation of explainable AI for fetal growth scans through multi-level, cross-institutional prospective end-user evaluation.

We aimed to develop and evaluate Explainable Artificial Intelligence (XAI) for fetal ultrasound usin...

Precision fetal cardiology detects cyanotic congenital heart disease using maternal saliva metabolome and artificial intelligence.

Prenatal sonographic diagnosis of congenital heart disease (CHD) can lead to improved morbidity and ...

Differences in technical and clinical perspectives on AI validation in cancer imaging: mind the gap!

Good practices in artificial intelligence (AI) model validation are key for achieving trustworthy AI...

Patch-Wise Deep Learning Method for Intracranial Stenosis and Aneurysm Detection-the Tromsø Study.

Intracranial atherosclerotic stenosis (ICAS) and intracranial aneurysms are prevalent conditions in ...

Deep Network Regularization for Phase-Based Magnetic Resonance Electrical Properties Tomography With Stein's Unbiased Risk Estimator.

Magnetic resonance imaging (MRI) can estimate tissue conductivity values using phase-based magnetic ...

The global research of magnetic resonance imaging in Alzheimer's disease: a bibliometric analysis from 2004 to 2023.

BACKGROUND: Alzheimer's disease (AD) is a common neurodegenerative disorder worldwide and the using ...

Deep Learning Radiomics Nomogram Based on MRI for Differentiating between Borderline Ovarian Tumors and Stage I Ovarian Cancer: A Multicenter Study.

RATIONALE AND OBJECTIVES: To develop and validate a deep learning radiomics nomogram (DLRN) based on...

LMSST-GCN: Longitudinal MRI sub-structural texture guided graph convolution network for improved progression prediction of knee osteoarthritis.

BACKGROUND AND OBJECTIVES: Accurate prediction of progression in knee osteoarthritis (KOA) is signif...

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