Radiology

Dual-representation structural MRI classification of psychiatric disorders using deep learning and large language models.

Accurate differentiation among psychiatric disorders such as schizophrenia and bipolar disorder remains a significant clinical challenge due to overlapping symptoms and subtle neuroanatomical variations. This study proposes a dual-representation structural MRI framework in which raw T1-weighted MRI slices and their corresponding color-coded tissue segmentation maps-both derived from the same imagi...

A novel framework for fully automated co-registration of intravascular ultrasound and optical coherence tomography imaging data.

AIMS: To develop a deep-learning (DL) framework that enables fully automated longitudinal and circumferential co-registration of intravascular ultrasound (IVUS) and optical coherence tomography (OCT) images. METHODS AND RESULTS: Data from 230 patients (714 vessels) with acute myocardial infarction that underwent near-infrared spectroscopy IVUS and OCT imaging in their non-infarct related vessels w...

Radiologist burnout: AI's true black box.

Multiple articles have touted the longitudinal promise of artificial intelligence (AI) in radiology, including projections of streamlining repetitive ...

Multisequence MRI Enables High-Fidelity FDG-PET Synthesis for Epilepsy Using GANs.

BACKGROUND: FDG-PET aids presurgical epilepsy evaluation but is limited by access and radiation exposure. PURPOSE: To evaluate synthetic FDG-PET gener...

AI-Based CT Image Recognition With Med-Gemini-3D in the Diagnosis of a Rare Craniofacial Condition: A Catlin Mark Skull.

Artificial intelligence (AI) is increasingly applied in diagnostic imaging to enhance pattern recognition and support clinical decision-making. In 202...

The real world of Italian new-generation radiologists: challenges and career expectations.

PURPOSE: To assess the perceived work-life balance, sources of job dissatisfaction, and career aspirations in the new generation of residents and youn...

Highly Undersampled MRI Reconstruction via a Single Posterior Sampling of Diffusion Models.

Incoherent k-space undersampling and deep learning-based reconstruction methods have shown great success in accelerating MRI. However, the performance...

The Diagnostic Value of Image-Based Machine Learning for Osteoporosis: Systematic Review and Meta-Analysis.

BACKGROUND: Osteoporosis (OP) is projected to be a major issue significantly impacting the well-being of middle-aged and old populations. Machine lear...

Using Latent Dirichlet Allocation Topic Modeling to Uncover Latent Research Topics and Trends in Renal Cell Carcinoma: Bibliometric Review.

BACKGROUND: Renal cell carcinoma (RCC) is a common, often lethal kidney cancer that originates in the renal cortex. Its incidence is rising, and major...

Magnetic resonance imaging-based proton dose calculation for pelvic tumors using deep learning.

Objective Magnetic resonance imaging (MRI)-only proton therapy combines high soft tissue contrast with high-precision dose distributions. However,...

Automated 4D flow MRI pipeline for the quantification of advanced hemodynamic parameters in the left atrium.

The left atrium (LA) plays a pivotal role in modulating left ventricular filling, yet its hemodynamics remain poorly understood due to the limitations...

Plasma glutamic acid predicts myelosuppression and mortality in septic patients using machine learning.

Myelosuppression is a common secondary manifestation of sepsis and is associated with increased morbidity and mortality. Recent evidence suggests that...

An attention-augmented multimodal classification of alzheimer's disease and parkinson's disease vs healthy controls using MRI, EEG, and SNP data.

Due to the late manifestation of structural symptoms and symptomatic overlap, neurodegenerative diseases such as Parkinson's Disease (PD) and Alzheime...

Survival and Surrogate Biomarkers in Interventional Oncology Trials: Pitfalls, Challenges, and Future Directions.

INTRODUCTION: Interventional oncology (IO) is a key component of multidisciplinary cancer care, delivering minimally invasive therapies with safety an...

Artificial intelligence in bladder cancer management: a narrative review of diagnostic and surgical advances and current limitations.

INTRODUCTION: Bladder cancer (BC) is associated with high recurrence and progression rates that require intensive surveillance. In this context, Artif...

Sex Differences in Alzheimer's Disease: A Systematic Review of Two Decades of Neuroimaging Research.

OBJECTIVES: Given the heterogeneous nature of Alzheimer's Disease (AD) and its higher prevalence in females, it is crucial to understand sex-related d...

Meteorological associations with out-of-hospital cardiac arrest: A national population-based time-series analysis.

OBJECTIVES: Meteorological factors may influence cardiovascular emergency incidence, but comprehensive national evidence for out-of-hospital cardiac a...

Impact of a new deep-learning image reconstruction algorithm on potential dose reduction and quality of chest CT images: a phantom study.

PURPOSE: To evaluate the impact of a new deep-learning image reconstruction (DLR) algorithm on image quality and potential dose reduction compared wit...

A graph-based spatio-temporal framework for predicting safety-critical pedestrian-vehicle interactions at unsignalized crosswalks.

Pedestrian safety remains a critical global concern, especially in countries like India, where unsignalized crossings with limited traffic control con...

Generalizable Deep Learning for Prostate Cancer Risk Stratification: Multicenter Study Integrating 18F-PSMA-1007 PET/CT and mpMRI.

BACKGROUND: Prostate cancer is the second most common cancer in men, with rising mortality rates necessitating precise risk stratification. High-invas...