Radiology

Predicting Late Gadolinium Enhancement of Acute Myocardial Infarction in Contrast-Free Cardiac Cine MRI Using Deep Generative Learning.

BACKGROUND: Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) is a standard techniq...

From Gadolinium to Generative AI: The Quest for Contrast-Free Cardiac Imaging.

A Pre-Voiding Alarm System Using Wearable Ultrasound and Machine Learning Algorithms for Children With Nocturnal Enuresis.

Nocturnal enuresis is a bothersome condition that affects many children and their caregivers. Post-v...

Evaluating text and visual diagnostic capabilities of large language models on questions related to the Breast Imaging Reporting and Data System Atlas 5 edition.

PURPOSE: This study aimed to evaluate the performance of large language models (LLMs) and multimodal...

Artificial intelligence system for identification of overlooked lung metastasis in abdominopelvic computed tomography scans of patients with malignancy.

PURPOSE: This study aimed to evaluate whether an artificial intelligence (AI) system can identify ba...

An efficient ranking-based ensembled multiclassifier for neurodegenerative diseases classification using deep learning.

Neurodegenerative diseases are group of debilitating and progressive disorders that primarily affect...

Artificial intelligence and advanced MRI techniques: A comprehensive analysis of diffuse gliomas.

INTRODUCTION: The complexity of diffuse gliomas relies on advanced imaging techniques like MRI to un...

Precise ablation zone segmentation on CT images after liver cancer ablation using semi-automatic CNN-based segmentation.

BACKGROUND: Ablation zone segmentation in contrast-enhanced computed tomography (CECT) images enable...

Training robust T1-weighted magnetic resonance imaging liver segmentation models using ensembles of datasets with different contrast protocols and liver disease etiologies.

Image segmentation of the liver is an important step in treatment planning for liver cancer. However...

Real-World Adoption of Artificial Intelligence in Radiology: Opportunities and Barriers.

Artificial Intelligence in the Training of Radiology Residents: a Multicenter Randomized Controlled Trial.

The aim of the present study was to compare the effectiveness of AI-assisted training and convention...

Reducing energy consumption in musculoskeletal MRI using shorter scan protocols, optimized magnet cooling patterns, and deep learning sequences.

OBJECTIVES: The unprecedented surge in energy costs in Europe, coupled with the significant energy c...

The Potential of Gemini and GPTs for Structured Report Generation based on Free-Text F-FDG PET/CT Breast Cancer Reports.

RATIONALE AND OBJECTIVE: To compare the performance of large language model (LLM) based Gemini and G...

Advancements in supervised deep learning for metal artifact reduction in computed tomography: A systematic review.

BACKGROUND: Metallic artefacts caused by metal implants, are a common problem in computed tomography...

Clinical impact of AI in radiology department management: a systematic review.

PURPOSE: Artificial intelligence (AI) has revolutionized medical diagnosis and treatment. Breakthrou...

Low-dose computed tomography perceptual image quality assessment.

In computed tomography (CT) imaging, optimizing the balance between radiation dose and image quality...

Topology-preserving segmentation of abdominal muscle layers from ultrasound images.

BACKGROUND: In clinical anesthesia, precise segmentation of muscle layers from abdominal ultrasound ...

Artificial intelligence in Ultrasound: Pearls and pitfalls in 2024.

Artificial intelligence-assisted measurements of coronary computed tomography angiography parameters such as stenosis, flow reserve, and fat attenuation for predicting major adverse cardiac events in patients with coronary arterial disease.

Advancements in artificial intelligence (AI) offer promising tools for improving diagnostic accuracy...

Precision meets generalization: Enhancing brain tumor classification via pretrained DenseNet with global average pooling and hyperparameter tuning.

Brain tumors pose significant global health concerns due to their high mortality rates and limited t...

Multifunctional aggregation network of cell nuclei segmentation aiming histopathological diagnosis assistance: A new MA-Net construction.

Automated diagnostic systems can enhance the accuracy and efficiency of pathological diagnoses, nucl...