Radiology

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

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MIL-PF: Multiple Instance Learning on Precomputed Features for Mammography Classification

Modern foundation models provide highly expressive visual representations, yet adapting them to high...

GIIM: Graph-based Learning of Inter- and Intra-view Dependencies for Multi-view Medical Image Diagnosis

Computer-aided diagnosis (CADx) has become vital in medical imaging, but automated systems often str...

Association of Radiologic PPFE Change with Mortality in Lung Cancer Screening Cohorts

Background: Pleuroparenchymal fibroelastosis (PPFE) is an upper lobe predominant fibrotic lung abnor...

Physics-Driven 3D Gaussian Rendering for Zero-Shot MRI Super-Resolution

High-resolution Magnetic Resonance Imaging (MRI) is vital for clinical diagnosis but limited by long...

TriFusion-SR: Joint Tri-Modal Medical Image Fusion and SR

Multimodal medical image fusion facilitates comprehensive diagnosis by aggregating complementary str...

FetalAgents: A Multi-Agent System for Fetal Ultrasound Image and Video Analysis

Fetal ultrasound (US) is the primary imaging modality for prenatal screening, yet its interpretation...

CycleULM: A unified label-free deep learning framework for ultrasound localisation microscopy

Super-resolution ultrasound via microbubble (MB) localisation and tracking, also known as ultrasound...

Adaptive Clinical-Aware Latent Diffusion for Multimodal Brain Image Generation and Missing Modality Imputation

Multimodal neuroimaging provides complementary insights for Alzheimer's disease diagnosis, yet clini...

Unsupervised Domain Adaptation with Target-Only Margin Disparity Discrepancy

In interventional radiology, Cone-Beam Computed Tomography (CBCT) is a helpful imaging modality that...

Multi-Kernel Gated Decoder Adapters for Robust Multi-Task Thyroid Ultrasound under Cross-Center Shift

Thyroid ultrasound (US) automation couples two competing requirements: global, geometry-driven reaso...

Vision-Language Models Encode Clinical Guidelines for Concept-Based Medical Reasoning

Concept Bottleneck Models (CBMs) are a prominent framework for interpretable AI that map learned vis...

Geometric Brain Signatures for Diagnosing Rare Hereditary Ataxias and Predicting Function

Hereditary cerebellar ataxias (HCAs) are rare neurodegenerative disorders characterised by progressi...

OSCAR: Occupancy-based Shape Completion via Acoustic Neural Implicit Representations

Accurate 3D reconstruction of vertebral anatomy from ultrasound is important for guiding minimally i...

Rectified flow-based prediction of post-treatment brain MRI from pre-radiotherapy priors for patients with glioma

Purpose/Objective: Brain tumors result in 20 years of lost life on average. Standard therapies induc...

DECADE: A Temporally-Consistent Unsupervised Diffusion Model for Enhanced Rb-82 Dynamic Cardiac PET Image Denoising

Rb-82 dynamic cardiac PET imaging is widely used for the clinical diagnosis of coronary artery disea...

A Semi-Supervised Framework for Breast Ultrasound Segmentation with Training-Free Pseudo-Label Generation and Label Refinement

Semi-supervised learning (SSL) has emerged as a promising paradigm for breast ultrasound (BUS) image...

Agentic retrieval-augmented reasoning reshapes collective reliability under model variability in radiology question answering

Agentic retrieval-augmented reasoning pipelines are increasingly used to structure how large languag...

3D CBCT Artefact Removal Using Perpendicular Score-Based Diffusion Models

Cone-beam computed tomography (CBCT) is a widely used 3D imaging technique in dentistry, offering hi...

K-MaT: Knowledge-Anchored Manifold Transport for Cross-Modal Prompt Learning in Medical Imaging

Large-scale biomedical vision-language models (VLMs) adapted on high-end imaging (e.g., CT) often fa...

GreenRFM: Toward a resource-efficient radiology foundation model

The development of radiology foundation models (RFMs) is hindered by a reliance on brute-force scali...

Artificial Intelligence for Detecting Fetal Orofacial Clefts and Advancing Medical Education

Orofacial clefts are among the most common congenital craniofacial abnormalities, yet accurate prena...

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