Radiology

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

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GCE-MIL: Faithful and Recoverable Evidence for Multiple Instance Learning in Whole-Slide Imaging

Multiple instance learning (MIL) is the standard approach for whole-slide image (WSI) classification...

CasualSynth: Generating Structurally Sound Synthetic Data

Large Language Models (LLMs) generate realistic synthetic data but offer no guarantee that their out...

Reliable Uncertainty Under Class Imbalance and Distribution Shift: Class-Conditional Conformal Prediction of Multiple Sclerosis

Objectives To evaluate whether class-conditional conformal prediction (CP) can provide reliable unce...

Deep Learning for Automated Meningioma Segmentation: Toward Clinical Integration and Workflow Efficiency

Background: Meningiomas are the most common primary intracranial tumors in adults, and volumetric as...

Automatic Landmark-Based Segmentation of Human Subcortical Structures in MRI

Precise segmentation of brain structures in magnetic resonance imaging (MRI) is essential for reliab...

Integration of immunomonitoring assays with PET/CT in TB patients identifies on-treatment biomarkers

Tuberculosis (TB) continues to pose a significant global public health challenge with substantial mo...

Towards Real-Time Autonomous Navigation: Transformer-Based Catheter Tip Tracking in Fluoroscopy

Purpose: Mechanical thrombectomy (MT) improves stroke outcomes, but is limited by a lack of local tr...

A CUBS-Compatible Ultrasound Morphology and Uncertainty-Aware Baseline for Carotid Intima-Media Segmentation and Preliminary Risk Prediction

Carotid atherosclerosis is a major contributor to ischemic stroke and transient ischemic attack. Con...

Separating Intrinsic Ambiguity from Estimation Uncertainty in Deep Generative Models for Linear Inverse Problems

Recently, deep generative models have been used for posterior inference in inverse problems, includi...

Prediction of Pivot Shift Grade Using In-Vivo Ultrasound Bone Tracking During Sit-Stand-Sit: A Machine Learning Feasibility Study

Background: The pivot shift (PS) test is the most specific clinical examination for anterolateral ro...

Contactless ultrasound chest vibration mapping discriminates respiratory and cardiac patients from healthy individuals.

Contactless assessment of cardiopulmonary function remains an unmet need, with current approaches re...

NexOP: Joint Optimization of NEX-Aware k-space Sampling and Image Reconstruction for Low-Field MRI

Modern low-field magnetic resonance imaging (MRI) technology offers a compelling alternative to stan...

Pyramid Self-contrastive Learning Framework for Test-time Ultrasound Image Denoising

The inherent electronic and speckle noise complicates clinical interpretation of ultrasound images. ...

When Brains Disagree: Biological Ambiguity Underlies the Challenge of Amyloid PET Synthesis from Structural MRI

Structural MRI-to-amyloid PET synthesis has been proposed as a non-invasive alternative for amyloid ...

Optimization in Sparse 2D to Dense 3D Weakly Supervised Learning: Application to Multi-Label Segmentation of Large ex vivo MRI Data

INTRODUCTION | Fully supervised 3D segmentation of high-resolution ex vivo MRI is limited by the pro...

MRI reveals the hierarchical organization of abdominal biological aging from shared burden to disease-specific organ engagement

Multi-organ biological aging is often represented as parallel organ-specific clocks, but how age gap...

Development of a Deep Learning Model Integrating CT Images and Blood Data for the Diagnosis of Acute Cholecystitis

Purpose: In this study, we aimed to develop and evaluate an artificial intelligence-based diagnostic...

An fMRI dataset of verbalized spontaneous thought with annotated transcripts and self-report trait measures

Spontaneous thought is pervasive in everyday human cognition, yet datasets capturing its neural dyna...

Talk2QSP: Deriving Executable Scenarios from Unstructured Literature via Human-in-the-Loop Agents

Quantitative Systems Pharmacology (QSP) models play an inherently interventional role in pharmaceuti...

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