Radiology

Feasibility of Free-breathing Deep Learning-reconstructed Single-Shot Cine MRI in Participants with Arrhythmia: Comparison with Conventional Segmented Cine MRI.

Purpose To evaluate the feasibility of retrospective electrocardiographically (ECG) gated single-shot cine using deep learning-enhanced compressed sensing (AI-CS) versus conventional balanced steady-state free precession (bSSFP) cine, focusing on left ventricular (LV) structure and function. Materials and Methods Between September 1, 2023, and September 28, 2024, participants (including those with...

ICECREAM: high-fidelity equivariant cryo-electron tomography.

Cryo-electron tomography (cryo-ET) visualizes 3D cellular architecture in its near-native state. The various deep-learning methods have improved denoising and artifact correction, but remain challenged by a very low signal-to-noise ratio, a restricted tilt range (`missing wedge') and the lack of ground truth. Here, we present ICECREAM, which bridges earlier self-supervised methods with the recent ...

Deep Learning for Automated Tumor Segmentation of Rectal Cancer on T2-Weighted Magnetic Resonance Images.

PURPOSE: To develop a deep learning (DL)-based automated segmentation model for rectal cancer on T2-weighted (T2W) magnetic resonance (MR) images. MAT...

Retrieval-Augmented Language Models for Patient-Centered Periprocedural Anticoagulation in Interventional Radiology.

PURPOSE: This study evaluates Large Language Models (LLMs) integrated with Retrieval-Augmented Generation (RAG) frameworks for generating accurate, gu...

Impact of a Digital Intelligence Platform on Radiology Workflow Efficiency and Patient Satisfaction: A Retrospective Cohort Study.

RATIONALE AND OBJECTIVES: Traditional radiology management models may face challenges in meeting the growing demand for medical imaging services, pote...

Large Language Models in Clinical Decision Support: A Comparative Analysis of Chat-GPT and Breast Radiologists on ACR Appropriateness Criteria.

RATIONALE AND OBJECTIVES: This study evaluates the performance of ChatGPT, a large language model (LLM), in selecting appropriate imaging modalities f...

Automating the segmentation, date extraction, and classification of multi-report PDFs in outside medical records using optical character recognition and generative artificial intelligence.

OBJECTIVES: Patients referred for specialized care often arrive with outside medical records (OMRs) compiled into multi-report PDFs that include imagi...

Efficient denoising in LED-based optoacoustic tomography with squeeze-and-excitation deep convolutional networks.

SIGNIFICANCE: Low-cost optoacoustic imaging based on light-emitting diodes (LEDs) offers an affordable alternative to traditional laser-based systems,...

Pre-heart failure in early chronic kidney disease: clinical epidemiology and treatment.

Chronic kidney disease (CKD), defined per the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines by persistent (≥3 months) abnormalities of ...

Artificial Intelligence-Assisted Ultrasound in Austere Trauma Environments: Implications for Role 1 Military Medicine.

Pararescue jumpers are United States Air Force medical tactical operators who provide advanced trauma and prolonged casualty care in austere, high-ris...

KidMesh: Computational Mesh Reconstruction for Pediatric Congenital Hydronephrosis Using Deep Neural Networks.

Pediatric congenital hydronephrosis (CH) is a common urinary tract disorder, primarily caused by obstruction at the renal pelvis-ureter junction. Magn...

Multi-label Ensemble Model for Knee Joint Anatomy and Lesion Segmentation: Segmentation of Clinical Images With Ensembling, Morphology, and Attention (SCEMA).

PURPOSE: Quantitative MRI analysis holds significant promise for improving the early diagnosis and prognosis of osteoarthritis (OA), where accurate ti...

Automatic Detection of Multiple Artifacts in Computed Tomography Images by Self-Attention Guided Vision Transformer.

Automated detection of image artifacts is crucial for enhancing the efficiency and quality of computed tomography (CT) workflows. This study presents ...

An echo from the past: open access repository of over 10,000 annotated Doppler audio recordings of venous gas emboli.

INTRODUCTION: Doppler ultrasound measurements have been recorded since the 1970s across the world and provide a valuable data resource for learning, a...

Robotics in Interventional Oncology: A Call to Arms?

Discovery of WRN helicase inhibitors by 3D-CNN docking and ML consensus from traditional Chinese medicine monomers.

The Werner syndrome (WRN) helicase is a validated synthetic-lethal vulnerability in cancers with microsatellite instability (MSI), making WRN inhibiti...

Integrating multi-omics data and artificial intelligence for personalized medicine in glioblastoma.

Glioblastoma (GBM) is one of the most lethal primary brain tumors and is characterized by profound molecular heterogeneity, rapid progression, and lim...

Review of agentic artificial intelligence (AI) in radiology: from current clinical integration to future innovations.

AIM: Artificial intelligence (AI) is one of the most revolutionary developments in the field of medicine in recent history, with radiology being one o...

Artificial Intelligence-Enhanced Cardiac Point-of-Care Ultrasound: A Prospective Single-Arm Study.

OBJECTIVE: To evaluate the clinical utility of combining artificial intelligence (AI) with handheld focused cardiac ultrasound (FoCUS) performed by no...

The oral-gut microbiome axis in diabetes mellitus: a systematic review and emerging clinical perspectives.

Emerging evidence suggests that diabetes mellitus (DM) is not only a metabolic disorder but also a mucosal disease shaped by microbial interactions ac...