Radiology

Latest AI and machine learning research in radiology for healthcare professionals.

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Evaluating Conversational Image Segmentation for Medicine: Performance, Failure Modes, and a Fairness Audit Across Seven Modalities

Medical-image segmentation underpins quantitative diagnostics and research, yet state-of-the-art mod...

Advancing Breast Cancer-AI Diagnostics: An Explainable Deep Learning Model Using 2D Grayscale Ultrasound Imaging

Breast cancer stands as the primary reason for fatality in female patients from cancer worldwide. Th...

Quantum-Enhanced Transfer Learning for MS Lesion Detection in MRI: A Hybrid Classical-Quantum Framework

Accurate detection of multiple sclerosis (MS) lesions in magnetic resonance imaging (MRI) requires r...

Enhancing MRI Safety: Real-Time Thermal Imaging Integrated with Deep Learning for Burn Prevention

Radiofrequency (RF)-induced burns are the most common MRI-related adverse event. Standard safety pra...

CSF Proteomics and Machine Learning Reveal Distinct Stages Across the Alzheimer’s Disease Continuum

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by heterogeneous pathophysiol...

Automatic detection of simulated artifacts on T1w magnetic resonance images: comparing performance of different QC strategies

The reliability of MRI-derived measures critically depends on image quality. Poor-quality scans can ...

Developing a Fully Automated Imaging Biomarker for HCC Risk Assessment via MRI-Based Tumor Segmentation and EPM

This study investigates the feasibility of using automated tumor segmentation as the region of inter...

GlioMODA: Robust Glioma Segmentation in Clinical Routine

Precise glioma segmentation in MRI is essential for accurate diagnosis, optimal treatment planning, ...

Circulating microglia-derived extracellular vesicles predict recovery after rehabilitation in stroke survivors

Timely intensive rehabilitation is crucial to contrast the negative escalation of events that follow...

Scaling genetic discovery for organ volumes using machine learning-assisted imputation and bias-corrected GWAS

MRI-derived organ and tissue volumes are powerful endophenotypes for studying complex disease, but t...

The Silent Signal: Unmasking Myocardial Ischemia in a Resting Heartbeat with Machine Learning

Ischemic heart disease (IHD) remains the leading cause of morbidity and mortality worldwide, imposin...

DeepFLAIR*: Improving Multiple Sclerosis Diagnostic Imaging Workflow Using Deep Learning

Magnetic resonance imaging (MRI) plays a central role in diagnosing multiple sclerosis (MS), yet con...

Network-based Molecular Constraints on in vivo Synaptic Density Alterations in Schizophrenia

Converging neuroimaging, genetic, and post-mortem evidence highlights the fundamental role of synapt...

Synthesizing Contrast-Enhanced T1 MR Image Using Multiparametric Sequences and Attention to Brain Tumor

The administration of gadolinium-based contrast agents (GBCAs) for acquiring contrast-enhanced T1-we...

Machine learning-based prediction of future dementia using routine clinical MRI brain scans and healthcare data

Early identification of dementia risk is essential for preventive care and timely enrolment into dis...

Enhanced Detection Rate of AI for Lung Cancer Detection on GP-Referred Chest X-rays: A Real-World Retrospective Evaluation

To assess whether an artificial intelligence (AI) chest radiograph (CXR) tool could enhance lung can...

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