Radiology

Real-Time, Inline Quantitative MRI Enabled by Scanner-Integrated Machine Learning: A Proof of Principle With NODDI.

PURPOSE: The clinical feasibility and translation of many advanced quantitative MRI (qMRI) techniques are inhibited by their restriction to 'research mode', due to resource-intensive, offline parameter estimation. This work aimed to achieve 'clinical mode' qMRI, by real-time, inline parameter estimation with a trained neural network (NN) fully integrated into a vendor's image reconstruction enviro...

The AROMA dataset for automatic detection of artifact type and severity in retinal optical coherence tomography angiography.

INTRODUCTION: In recent years, retinal vascular imaging has attracted growing interest and is experiencing rapid technological advancements in imaging modalities such as swept-source optical coherence tomography angiography (SS OCT-A). OCT-A enables precise, noninvasive, quantitative measurements of retinal vascularization. However, it is also prone to artifacts that are challenging to detect and ...

Development and validation of a machine learning model to predict recurrence in polypoidal choroidal vasculopathy: a multicentre prospective study.

AIM: This study aims to develop and validate machine learning models for predicting recurrence in polypoidal choroidal vasculopathy (PCV) patients usi...

Classification of retinal diseases based on optical coherence tomography angiography using cross-modal transfer learning of domain-specific foundation AI models.

AIMS: This study evaluated the use of ophthalmic foundation deep-learning models with cross-modal transfer learning to classify multiple diseases on o...

Machine learning for the prediction of three-year survival in locally advanced breast cancer patients receiving neoadjuvant chemotherapy using quantitative ultrasound imaging.

Locally Advanced Breast Cancer (LABC) is a serious type of cancer with a poor prognosis despite advances in cancer treatment. As the disease is often ...

Comparing artificial intelligence and physician performance in predicting IDH mutation status in glioma.

Predicting isocitrate dehydrogenase (IDH) mutations in gliomas using magnetic resonance imaging (MRI) is clinically important for treatment planning. ...

Pancreatic tumor detection in computed tomography images through a rotary positional siamese vision transformer.

Vision Transformers (ViTs) are one of the powerful tools in medical imaging, providing new possibilities for pancreatic cancer diagnosis. In recent ye...

Prediction of tumor regression grading in rectal cancer neoadjuvant chemoradiotherapy: a habitat radiomics analysis of imaging biomarker.

BACKGROUND: Tumor regression grading (TRG) is a core prognostic predictor of treatment outcomes in rectal cancer. Conventional TRG assessment methods ...

Evaluating the clinical safety of large language models in oral cancer-related patient communication: a repeated-prompt observational study.

BACKGROUND: As patients increasingly consult large language models (LLMs) for health-related information, evaluating the clinical safety of AI-generat...

Executive summary of the 2026 consensus document. Planning the future of Internal Medicine: A position statement of the International Forum of Internal Medicine (FIMI).

The International Forum of Internal Medicine (FIMI) presents a position paper that analyzes the current state and projects the future of Internal Medi...

Intelligent diagnosis of major depressive disorder with edge convolution and contrastive learning.

Based on functional connectivity (FC) matrices derived from resting-state functional magnetic resonance imaging (rs-fMRI) data, graph neural networks ...

3D Freehand Ultrasound Reconstruction of the Carotid Artery.

OBJECTIVE: Sensorless alignment of two-dimensional (2D) freehand ultrasound scans for three-dimensional US (3DUS) reconstruction offers significant ad...

Ultrasound Microvascular Imaging Using Deep Knowledge Distillation.

Ultrafast Doppler imaging provides critical insights into tissue perfusion but traditionally requires long acquisitions and computationally expensive ...

MRI Deep Learning for Differentiating Glioblastoma, IDH-Wildtype from Central Nervous System Diffuse Large B-cell Lymphoma.

Glioblastoma, IDH-wildtype (GBM) and central nervous system diffuse large B-Cell lymphoma (CNS-DLBCL) are aggressive brain tumors with overlapping MRI...

High-Resolution 2D versus 3D Lumbar Spine MRI Optimized with a Deep Learning Reconstruction Algorithm and Prototype Conformal Coil.

BACKGROUND AND PURPOSE: Lumbar spine MRI is predominantly performed using 2D FSE sequences. 3D FSE sequences offer potential advantages over 2D, espec...

Deep Learning Radiomics Signature from Multicontrast MRI for Automated Identification of Symptomatic Carotid Plaques: A Multicenter Study.

BACKGROUND AND PURPOSE: Ischemic stroke poses a significant global health burden. Accurately identifying symptomatic carotid atherosclerotic plaques, ...

Mapping the body: poetic metaphor and AI imaging in Carol Ann Duffy's 'The Map-Woman'.

This article offers an interdisciplinary analysis of Carol Ann Duffy's poem 'The Map-Woman', examining the metaphor of the female body as a map in rel...

A large-scale 12-lead electrocardiogram dataset for acute coronary syndrome prediction containing 19,955 ECGs.

Acute coronary syndrome(ACS) is a common cardiovascular disease and a severe type of coronary heart disease. Electrocardiograms(ECGs) are the initial ...

Noninvasive molecular subtyping of breast cancer using multimodal ultrasound spatiotemporal transformer.

Molecular subtyping is essential for guiding systemic therapy in breast cancer but currently requires invasive biopsy. Conventional B-mode ultrasound ...

The absence of full lifecycle risk management for AI-based medical devices in radiology.

This study represents the systematic examination of full lifecycle management for radiology artificial intelligence medical (AI) devices approved by t...