Radiology

Global-Local Feature Fusion and SIREN-enhanced geometric supervision for coronary artery segmentation in CCTA.

Accurate segmentation of coronary arteries from Coronary Computed Tomography Angiography (CCTA) is essential for automated cardiovascular disease diagnosis and risk stratification. However, this task presents a fundamental global-local dilemma: modeling the topology and continuity of the extensive vascular tree requires wide-field contextual reasoning, while delineating thin, elongated distal bran...

Plant bioacoustics: decoding ultrasonic emissions.

For decades, plant-environment interactions were understood to be primarily mediated by chemical and visual stimuli. However, recent evidence has unveiled an underexplored dimension of plant physiology: airborne ultrasonic emissions. This review evaluates current research in plant bioacoustics, focusing on ultrasound generation, characteristic features, and specificity across different stress cond...

Artificial Intelligence Standardizes Pericoronary Fat Attenuation Index Measurement: External Multi-Vendor CT Validation.

OBJECTIVES: To evaluate the feasibility and generalizability of an AI-based automated method for measuring the pericoronary fat attenuation index (FAI...

Large language models and prostate MRI reporting: a stringent testbed for safe deployment under evolving AI, health-data, and cybersecurity regulation.

Prostate magnetic resonance imaging (MRI) reporting is a high-impact communication task because small differences in lesion laterality, sector localiz...

Evaluation of gastric cancer using artificial intelligence iterative reconstruction on abdominal CT: image quality and diagnostic accuracy.

PURPOSE: To investigate the clinical performance of a novel deep-learning based image reconstruction algorithm, namely artificial intelligence iterati...

Detecting scoliosis at scale using automated cobb angle analysis in the UK biobank.

PURPOSE: Adult degenerative scoliosis arises after skeletal maturity in an initially normal spine, primarily driven by age-related degeneration. The C...

A multimodal MRI-based deep learning model for non-invasive diagnosis of pineal region germinoma.

ABRACTST: PURPOSE: To develop a deep learning model for the preoperative, non-invasive identification of germinomas in the pineal region. METHODS: Thi...

An AI-Supported Virtual Patient Application Using a Structured Prompting Framework to Develop Mental Status Examination Skills in Psychiatric Nursing Internship Students: An Interventional Mixed-Methods Study.

The aim of this study is to evaluate the effect of an artificial intelligence (AI)-powered virtual patient application (ChatGPT) on the development of...

Motion Artifact-Aware Self-Supervised Representation Learning for 3D Brain MRI Motion Artifact Reduction.

Patient motion remains a source of image degradation in brain MRI, leading to signal loss, blurring, and geometric distortion that compromise quantita...

Development and clinical validation of a point-of-care cytology screening tool for oral potentially malignant disorders and oral squamous cell carcinoma using a deep learning convolutional neural network: protocol for a diagnostic accuracy study.

INTRODUCTION: Oral potentially malignant disorders (OPMDs) and oral squamous cell carcinoma (OSCC) present a remarkable public health challenge worldw...

Deep Learning-Accelerated 3D Vessel Wall MRI: Prospective Evaluation of Sonic DL with Substantial Scan Time Reduction.

PURPOSE: While 3D vessel wall MRI (VW-MRI) is essential for characterizing vasculopathies, prolonged acquisition times limit its utility by increasing...

Clustering analysis of hamstring injuries-A pilot study to determine phenogroups based on injury characteristics and recovery duration.

PURPOSE: The objective of this pilot study was to determine clinically relevant phenogroups of professional football players with hamstring injuries u...

Deep Learning-Accelerated MRI Assessment of Hepatic Proton Density Fat Fraction: Agreement With Conventional Acquisition Across Manual and Automated Measurement Approaches.

BACKGROUND: Deep learning reconstruction can shorten breath-hold MRI for liver proton density fat fraction (DL-PDFF), but agreement with conventional ...

Multiscale Multiparametric MRI Deep Learning for Short-Term Survival Assessment in Glioblastoma.

BACKGROUND: Preoperative identification of short-term survival in glioblastoma may guide management but remains challenging because of clinical and im...

Automated diagnostic system for classification of progression stages of osteoarthritis using magnetic resonance imaging.

INTRODUCTION: Osteoarthritis (OA) is a degenerative joint disease characterized by cartilage loss, synovial fluid imbalance, and bone structural chang...

A Dual-Center, Interpretable Deep Learning-Radiomics Fusion Model for Distinguishing Nasopharyngeal Carcinoma from Nasopharyngeal Lymphoma Using FDG PET/CT.

RATIONALE AND OBJECTIVES: Accurate differentiation between Nasopharyngeal Carcinoma (NPC) and Nasopharyngeal Lymphoma (NPL) is critical for clinical m...

A Combined Deep Learning Approach to Screen Patients for Neuromuscular Pathology.

Neuromuscular diseases (NMD), comprising over 600 different conditions, severely impact nerve and/or muscle function and lead to significant morbidity...

Artificial Intelligence-Assisted Contrast-Enhanced Ultrasound for Perfusion Evaluation: State-of-the-Art Review.

Accurate perfusion evaluation is crucial for clinical diagnosis and treatment, such as lesion characterization and risk stratification of carotid athe...

CT-based prediction of hematoma expansion and adverse outcomes after intracerebral hemorrhage: evidence appraisal, artificial intelligence translation, and GeroScience perspectives.

Spontaneous intracerebral hemorrhage (ICH) is a highly lethal and disabling form of stroke, in which hematoma expansion (HE) is a major and potentiall...

Anatomical Localization of Intracranial Electrodes Using Synthetic MRI Generated from Computed Tomography.

BACKGROUND AND OBJECTIVES: MRI and computed tomography (CT) are commonly combined to localize intracranial electrodes in deep brain stimulation (DBS)....