Radiology

Automated Deep Learning-based Segmentation of the Dentate Nucleus Using Quantitative Susceptibility Mapping MRI.

Purpose To develop a dentate nucleus (DN) segmentation tool using deep learning (DL) applied to bra...

Segmenting Whole-Body MRI and CT for Multiorgan Anatomic Structure Delineation.

Purpose To develop and validate MRSegmentator, a retrospective cross-modality deep learning model f...

AI-Guided Cardiac Computer Tomography in Type 1 Diabetes Patients with Low Coronary Artery Calcium Score.

Cardiovascular risk stratification based on traditional risk factors lacks precision at the individ...

Fast Multi-Dimensional Imaging Using the Unsupervised 3D Noise2Void Denoising Network.

Label-free multidimensional imaging techniques are widely used in biological imaging. Among them, Ra...

Preserving the Cognitive Process: Rethinking Radiology Education in the Age of Artificial Intelligence.

Deep learning based localisation and classification of gamma photon interactions in thick nanocomposite and ceramic monolithic scintillators.

Accurate localisation of the first point of interaction (FPoI) of incident gamma photons in monolith...

Automated ultrasound system ARTHUR V.2.0 with AI analysis DIANA V.2.0 matches expert rheumatologist in hand joint assessment of rheumatoid arthritis patients.

OBJECTIVE: To evaluate the agreement and repeatability of an automated robotic ultrasound system (AR...

Digital Twins for Personalized Medicine Require Epidemiological Data and Mathematical Modeling: Viewpoint.

Digital twin (DT) technology is revolutionizing clinical practice by integrating diverse epidemiolog...

Innovative machine learning approach for liver fibrosis and disease severity evaluation in MAFLD patients using MRI fat content analysis.

This study employed machine learning models to quantitatively analyze liver fat content from MRI ima...

Imaging in clinical trials of rheumatoid arthritis: where are we in 2025?

Accurate detection and assessment of inflammatory activity is crucial not only for diagnosing patien...

Utilizing 3D fast spin echo anatomical imaging to reduce the number of contrast preparations in quantification of knee cartilage using learning-based methods.

PURPOSE: To propose and evaluate an accelerated quantification method that combines -weighted fast...

Brain tumor segmentation by optimizing deep learning U-Net model.

BackgroundMagnetic Resonance Imaging (MRI) is a cornerstone in diagnosing brain tumors. However, the...

AI-driven framework for automated detection of kidney stones in CT images: integration of deep learning architectures and transformers.

. Kidney stones, a prevalent urological condition, associated with acute pain requires prompt and pr...

Natural language processing for kidney ultrasound analysis: correlating imaging reports with chronic kidney disease diagnosis.

INTRODUCTION: Natural language processing (NLP) has been used to analyze unstructured imaging report...

Enhanced detection of ovarian cancer using AI-optimized 3D CNNs for PET/CT scan analysis.

This study investigates how deep learning (DL) can enhance ovarian cancer diagnosis and staging usin...

Impact of artificial intelligence assistance on bone scintigraphy diagnosis.

Bone scintigraphy is an important tool for detecting bone lesions. This study aimed to improve and e...

Digital Twin Technology In Radiology.

A digital twin is a computational model that provides a virtual representation of a specific physica...

Protecting Radiology Data and Devices Against Cybersecurity Threats: A Joint White Paper of the American College of Radiology (ACR) and Society for Imaging Informatics in Medicine (SIIM).

Modern radiology relies entirely on digital imaging systems. Healthcare records draw cybercriminals'...

Machine Learning and MRI-Based Whole-Organ Magnetic Resonance Imaging Score (WORMS): A Novel Approach to Enhancing Genicular Artery Embolization Outcomes in Knee Osteoarthritis.

PURPOSE: To evaluate the feasibility of machine learning (ML) models using preprocedural MRI-based W...

Diagnostic systematic review and meta-analysis of machine learning in predicting biochemical recurrence of prostate cancer.

Prostate cancer (PCa) is the most prevalent malignant tumor in males, and many patients remain at ri...

Retrospective evaluation of interval breast cancer screening mammograms by radiologists and AI.

OBJECTIVES: To determine whether an AI system can identify breast cancer risk in interval breast can...