Radiology

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

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CSV-ViT: A Vision Transformer with the Variable-sized Cortical Supervertices for Detection of Alzheimer's Disease Pathologies

Confirming Alzheimer's disease (AD) typically relies on positron emission tomography (PET), which re...

Cesarean Scar Defect Segmentation in Transvaginal Ultrasound Images: a Dataset and Benchmark

Cesarean Scar Defect (CSD) is one of the most prevalent complications following cesarean delivery. T...

Normative modeling for quantitative brain MRI phenotyping and biomarker discovery for pediatric leukodystrophies

Importance: Leukodystrophies are a heterogeneous group of genetic disorders affecting the white matt...

CausalFlow: Causal Attribution and Counterfactual Repair for LLM Agent Failures

Large language model (LLM) agents frequently fail on multi-step tasks involving reasoning, tool use,...

Towards Reliable Fetal Ultrasound Interpretation with Multi-Agent Collaboration

Automated fetal ultrasound interpretation requires a workflow from visual perception, including plan...

Subspace-Guided Semantic and Topological Invariant Registration for Annotation-Free Ultrasound Plane Quality Control

Reliable quality control (QC) of ultrasound images is essential for both real-time acquisition guida...

Anatomy-Anchored Self-Supervision: Distilling Vision Foundation Models for Invariant Ultrasound Representation

Self-supervised pre-training paradigm has gained increasing prominence for learning transferable rep...

Cross-Stage Attention Multi-Expert Network for Radiologist-Inspired Breast Ultrasound Diagnosis

Breast ultrasound imaging is an important noninvasive method for early breast cancer diagnosis, but ...

Artifact Correction for Echo-Planar Imaging at Low-Field and Ultra-Low-Field MRI

Purpose: Echo-planar imaging (EPI) in low-field (LF) and ultra-low-field MRI (ULF) suffers from seve...

How Far Has AI Come in Liver Fibrosis Staging? A Large-Scale Real-World Dataset and Benchmark

Despite years of methodological progress, how far AI has come in liver fibrosis staging has never be...

SAFE-Diff: Scale-Aware Attention and Feature-Dispersive Diffusion with Uncertainty Estimation for Contrast-Enhanced Breast MRI Synthesis

Synthesizing high fidelity contrast enhanced MRI is clinically valuable for safer and more efficient...

EchoPilot: Training-Free Ultrasound Video Segmentation via Scale-Space Semantic Prompting and Reliability-Gated Memory

Ultrasound video segmentation is clinically valuable yet difficult due to speckle noise, weak bounda...

Multimodal MRI and Machine Learning Uncovers Distinct Progression Patterns in Friedreich Ataxia

Background Friedreich ataxia (FRDA) is a rare neurodegenerative disorder with substantial heterogene...

Predicting Autopsy-Confirmed Neuropathology across Clinical, Neuroimaging, and CSF Biomarkers using Machine Learning

Accurate in vivo prediction of neuropathology is critical for advancing diagnosis and treatment of A...

Estimating bone marrow adiposity from head MRI and identifying its genetic architecture

Bone marrow adiposity changes radically through the lifespan, but this phenomenon is poorly characte...

Genetic architecture of high-dimensional liver radiomic phenotypes and their role in common metabolic diseases

The liver plays a central role in systemic metabolism, yet large-scale genetic studies of quantitati...

Virtual 3D H&E Staining from Phase-contrast Back-illumination Interference Tomography

Three-dimensional (3D) histopathology of unprocessed tissues has the potential to transform disease ...

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