Radiology

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

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Decoding fetal motion in 4D ultrasound with DeepLabCut.

PURPOSE: This study aimed to objectively and quantitatively analyze fetal motor behavior using DeepL...

Clinical research and trials in echocardiography: rationale, requirements and future opportunities.

Echocardiography has established itself as a vital component in the diagnosis and management of card...

Improving early detection of Alzheimer's disease through MRI slice selection and deep learning techniques.

Alzheimer's disease is a progressive neurodegenerative disorder marked by cognitive decline, memory ...

StarVasc: hyper-dimensional and spectral feature expansion for lightweight vascular enhancement.

Vascular contrast enhancement is crucial for early disease diagnosis and surgical precision in robot...

Dense breasts and women's health: which screenings are essential?

This review synthesizes current evidence regarding optimal breast cancer screening strategies for wo...

Supporting intraoperative margin assessment using deep learning for automatic tumour segmentation in breast lumpectomy micro-PET-CT.

Complete tumour removal is vital in curative breast cancer (BCa) surgery to prevent recurrence. Rece...

Collaborative and privacy-preserving cross-vendor united diagnostic imaging via server-rotating federated machine learning.

Federated Learning (FL) is a distributed framework that enables collaborative training of a server m...

The Quality of Information Produced by ChatGPT About Conditions Managed by Interventional Radiologists.

INTRODUCTION: The emergence of search engines powered by artificial intelligence and large language ...

Ultrasound-Based Machine Learning and SHapley Additive exPlanations Method Evaluating Risk of Gallbladder Cancer: A Bicentric and Validation Study.

OBJECTIVES: This study aims to construct and evaluate 8 machine learning models by integrating ultra...

Synthesized myelin and iron stainings from 7T multi-contrast MRI via deep learning.

Iron and myelin are key biomarkers for studying neurodegenerative and demyelinating brain diseases. ...

A Co-Plane Machine Learning Model Based on Ultrasound Radiomics for the Evaluation of Diabetic Peripheral Neuropathy.

RATIONALE AND OBJECTIVES: Detection of diabetic peripheral neuropathy (DPN) is critical for preventi...

Deep learning-based image enhancement for improved black blood imaging in brain metastasis.

OBJECTIVES: To evaluate the utility of a deep learning (DL)-based image enhancement for improving th...

Non-invasive prediction of the secondary enucleation risk in uveal melanoma based on pretreatment CT and MRI prior to stereotactic radiotherapy.

PURPOSE: The aim of this study was to develop a radiomic model to non-invasively predict the risk of...

BCDCNN: breast cancer deep convolutional neural network for breast cancer detection using MRI images.

Breast cancer (BC) is a kind of cancer that is created from the cells in breast tissue. This is a pr...

A Deep Learning Model to Detect Acute MCA Occlusion on High Resolution Non-Contrast Head CT.

BACKGROUND AND PURPOSE: To assess the feasibility and accuracy of a deep learning (DL) model to iden...

Deep unrolled primal dual network for TOF-PET list-mode image reconstruction.

OBJECTIVE: Time-of-flight (TOF) information provides more accurate location data for annihilation ph...

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