Radiology

Swin UNETR-based prediction of [68Ga]Ga-FAPI-46 PET/CT dose rate maps in cancer patients: quantitative comparison with [18F]FDG PET/CT.

BACKGROUND: Fibroblast activation protein (FAP) is a promising theranostic target due to its high stroma expression in numerous malignancies. This study presents the first DL-based framework for predicting dose rate maps (DRMs) from [68Ga]Ga-FAPI-46 PET/CT, following a quantitative and dosimetric comparison with [18F]FDG PET/CT. The approach supports personalized pre-therapeutic planning in radiop...

Artificial intelligence literacy and influencing factors among clinical nurses in southeastern China: a latent profile analysis.

BACKGROUND: The rapid integration of artificial intelligence (AI) in clinical settings presents unprecedented opportunities, yet it concurrently triggers significant challenges, including ethical dilemmas, technology-induced anxiety, and care quality. Although clinical nurses are the primary users of healthcare AI, their literacy levels and cognitive profiles remain largely unexplored. This knowle...

Masked autoencoder pretraining for peripheral nerve segmentation in ultrasound images.

Despite recent advances in medical image segmentation, deep learning applications in musculoskeletal ultrasound remain limited by small labeled datase...

Pre-operative MRI-Based Radiomics for Predicting Telomerase Reverse Transcriptase Promoter Mutation Status in Glioma Patients: A Systematic Review and Meta-analysis.

TERT promoter (TERTp) mutations shape glioma prognosis and therapy, yet tissue testing can be limited by sampling error and surgical inaccessibility. ...

Development and evaluation of deep learning models for automatic coronary stenosis segmentation in X-ray angiography.

Accurate segmentation of stenosis in X-ray angiography (XRA) images is crucial for the objective assessment of stenosis severity and subsequent treatm...

Exploring artificial intelligence in point-of-care and standard breast ultrasound: a paired reader study.

BackgroundBreast cancer diagnoses are limited in low- and middle-income settings due to lack of medical resources. In these settings, point-of-care ul...

Evaluation of standardized DICOM labels assigned by a hybrid AI tool and its impact on radiologists' reading times.

OBJECTIVES: Medical artificial intelligence (AI) tools are increasingly used to manage the growing imaging workload in radiology. Although highly rele...

Diagnostic accuracy of an artificial intelligence-based breast ultrasound tool in pregnant and lactating patients.

OBJECTIVES: To assess the diagnostic performance of an artificial intelligence (AI)-based decision support tool for breast ultrasound in pregnant and ...

Identifing two distinct cortical progression subtypes of Parkinson's disease through multimodal neuroimaging.

PURPOSE: To investigate whether distinct patterns of cortical involvement exist in Parkinson's disease (PD) and to characterize their potential progre...

Performance evaluation of deep learning based YOLOv5 and YOLOv8 models for real time breast cancer detection in mammographic images.

Breast cancer detection remains a significant challenge in medical diagnostics. Traditional diagnostic methods are time-consuming, unable to detect co...

Supervised autoencoder for gradient and BCG artifact removal in EEG during simultaneous EEG-fMRI.

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) provide complementary views of brain function, but MRI-indu...

Prospective validation of an AI algorithm to identify adult-onset type 1 diabetes misclassification: protocol for a non-interventional multicentre study.

INTRODUCTION: Adult-onset type 1 diabetes (T1D) is often misclassified as type 2 diabetes (T2D), resulting in delayed treatment, missed opportunities ...

QSM vs dopamine transporter PET: χ+ Mapping Shows Stronger Longitudinal Associations with Nigral Degeneration than Conventional QSM in Parkinson's Disease.

BACKGROUND: Iron accumulation in the substantia nigra (SN) is a hallmark of Parkinson's disease (PD). Quantitative susceptibility mapping (QSM) includ...

Quantification of Histotripsy Dosage Using Machine Learning-Enhanced Ultrasound Imaging Analysis: Correlation with Histological Outcomes.

RATIONALE AND OBJECTIVES: Histotripsy is a noninvasive ultrasound therapy that mechanically disrupts target tissue through controlled acoustic cavitat...

Hybrid vision transformer and ensemble machine learning framework for automated atherosclerotic plaque classification in intravascular ultrasound imaging.

Atherosclerotic plaque classification in intravascular ultrasound (IVUS) imaging is crucial for cardiovascular disease diagnosis and treatment plannin...

AI-assisted extraction of opportunistic findings from oncologic CT reports using large language models.

Opportunistic findings at imaging (iOFs), such as osteoporosis, liver steatosis, or coronary artery calcifications, are clinically relevant abnormalit...

Noninvasive PPROM risk stratification with explainable AI using routine antenatal CRP and albumin.

Premature rupture of membranes (PROM) and preterm PROM (PPROM) are significant obstetric complications, affecting 10-20% and 3% of pregnancies globall...

Deep Learning-Based Metal Artifact Reduction in Cardiac Computed Tomography: A Preliminary Study Enabling Radiomic Analysis in Patients with Implantable Defibrillators.

Idiopathic ventricular fibrillation (IVF) affects 5-10% of out-of-hospital cardiac arrest survivors, requiring implantable cardioverter-defibrillators...

Multi-scale feature integration with enhanced cytomorph for high-accuracy cervical cytology classification.

Accurate classification of cervical cytology images plays a crucial role in early detection and prevention of cervical cancer, which remains a signifi...

Advances in Ultrasound-Guided Fascial Plane Blocks for Perioperative Acute Pain Management.

INTRODUCTION: Perioperative acute pain remains a major challenge because conventional analgesic strategies are often limited by inadequate efficacy an...