Radiology

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

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DoseRAD2026 Challenge dataset: AI accelerated photon and proton dose calculation for radiotherapy

Purpose: Accurate dose calculation is essential in radiotherapy for precise tumor irradiation while ...

Representation geometry shapes task performance in vision-language modeling for CT enterography

Computed tomography (CT) enterography is a primary imaging modality for assessing inflammatory bowel...

Cross-Cohort Generalizability of Plasma Biomarker Machine Learning Models Reveals Calibration-Driven Degradation in Clinical Utility

BackgroundPlasma biomarkers demonstrate strong within-cohort performance for identifying cerebral am...

ReXSonoVQA: A Video QA Benchmark for Procedure-Centric Ultrasound Understanding

Ultrasound acquisition requires skilled probe manipulation and real-time adjustments. Vision-languag...

Evaluating the Impact of Medical Image Reconstruction on Downstream AI Fairness and Performance

AI-based image reconstruction models are increasingly deployed in clinical workflows to improve imag...

ReXSonoVQA: A Video QA Benchmark for Procedure-Centric Ultrasound Understanding

Ultrasound acquisition requires skilled probe manipulation and real-time adjustments. Vision-languag...

Cost-optimal Sequential Testing via Doubly Robust Q-learning

Clinical decision-making often involves selecting tests that are costly, invasive, or time-consuming...

Precision Synthesis of Multi-Tracer PET via VLM-Modulated Rectified Flow for Stratifying Mild Cognitive Impairment

The biological definition of Alzheimer's disease (AD) relies on multi-modal neuroimaging, yet the cl...

LoGo-MR: Screening Breast MRI for Cancer Risk Prediction by Efficient Omni-Slice Modeling

Efficient and explainable breast cancer (BC) risk prediction is critical for large-scale population-...

Exploring Radiologists' Expectations of Explainable Machine Learning Models in Medical Image Analysis

In spite of the strong performance of machine learning (ML) models in radiology, they have not been ...

MosaicMRI: A Diverse Dataset and Benchmark for Raw Musculoskeletal MRI

Deep learning underpins a wide range of applications in MRI, including reconstruction, artifact remo...

PERCEPT-Net: A Perceptual Loss Driven Framework for Reducing MRI Artifact Tissue Confusion

Purpose: Existing deep learning-based MRI artifact correction models exhibit poor clinical generaliz...

MedFormer-UR: Uncertainty-Routed Transformer for Medical Image Classification

To ensure safe clinical integration, deep learning models must provide more than just high accuracy;...

AMO-ENE: Attention-based Multi-Omics Fusion Model for Outcome Prediction in Extra Nodal Extension and HPV-associated Oropharyngeal Cancer

Extranodal extension (ENE) is an emerging prognostic factor in human papillomavirus (HPV)-associated...

MonoUNet: A Robust Tiny Neural Network for Automated Knee Cartilage Segmentation on Point-of-Care Ultrasound Devices

Objective: To develop a robust and compact deep learning model for automated knee cartilage segmenta...

Rotation Equivariant Convolutions in Deformable Registration of Brain MRI

Image registration is a fundamental task that aligns anatomical structures between images. While CNN...

Data-efficient Self-Supervised Diffusion Learning for Detecting Myofascial Pain in Upper Trapezius Muscle with B-mode Ultrasound Videos

Deep learning has transformed medical image and video analysis, but it usually requires large, well ...

VAMAE: Vessel-Aware Masked Autoencoders for OCT Angiography

Optical coherence tomography angiography (OCTA) provides non-invasive visualization of retinal micro...

Vision-Language Model-Guided Deep Unrolling Enables Personalized, Fast MRI

Magnetic Resonance Imaging (MRI) is a cornerstone in medicine and healthcare but suffers from long a...

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