Radiology

[Applications of artificial intelligence in radiology].

BACKGROUND: Artificial intelligence (AI) is increasingly finding its way into routine radiological w...

An Examination of Temporomandibular Joint Disc Displacement through Magnetic Resonance Imaging by Integrating Artificial Intelligence: Preliminary Findings.

This research was aimed at constructing a complete automated temporomandibular joint disc position ...

Ultrasonic Assessment of Liver Fibrosis Using One-Dimensional Convolutional Neural Networks Based on Frequency Spectra of Radiofrequency Signals with Deep Learning Segmentation of Liver Regions in B-Mode Images: A Feasibility Study.

The early detection of liver fibrosis is of significant importance. Deep learning analysis of ultras...

Artificial Intelligence and Cardiology Practice in Nigeria: Are We Ready?

Cardiovascular diseases are the leading cause of death globally. As cardiovascular risk factors cont...

Ultrasound-Based Deep Learning Radiomics Nomogram for Tumor and Axillary Lymph Node Status Prediction After Neoadjuvant Chemotherapy.

RATIONALE AND OBJECTIVES: This study aims to explore the feasibility of the deep learning radiomics ...

Integrated deep learning model for automatic detection and classification of stenosis in coronary angiography.

Coronary artery disease poses a significant threat to human health. In clinical settings, coronary a...

Polar contrast attention and skip cross-channel aggregation for efficient learning in U-Net.

The performance of existing lesion semantic segmentation models has shown a steady improvement with ...

Health inequities, bias, and artificial intelligence.

Musculoskeletal (MSK) pain leads to significant healthcare utilization, decreased productivity, and ...

Deep learning-based segmentation in MRI-(immuno)histological examination of myelin and axonal damage in normal-appearing white matter and white matter hyperintensities.

The major vascular cause of dementia is cerebral small vessel disease (SVD). Its diagnosis relies on...

Deep Learning With Ultrasound Images Enhance the Diagnosis of Nonalcoholic Fatty Liver.

OBJECTIVE: This research aimed to improve diagnosis of non-alcoholic fatty liver disease (NAFLD) by ...

Impact of Emerging Deep Learning-Based MR Image Reconstruction Algorithms on Abdominal MRI Radiomic Features.

OBJECTIVE: This study aims to evaluate, on one MRI vendor's platform, the impact of deep learning (D...

Reconstruct incomplete relation for incomplete modality brain tumor segmentation.

Different brain tumor magnetic resonance imaging (MRI) modalities provide diverse tumor-specific inf...

Incidental pulmonary nodules: Natural language processing analysis of radiology reports.

BACKGROUND: Pulmonary nodules are a common incidental finding on chest Computed Tomography scans (CT...

Radiology staff perspectives are a key determinant for successful AI adoption in clinical practice.

ATOMMIC: An Advanced Toolbox for Multitask Medical Imaging Consistency to facilitate Artificial Intelligence applications from acquisition to analysis in Magnetic Resonance Imaging.

BACKGROUND AND OBJECTIVES: Artificial intelligence (AI) is revolutionizing Magnetic Resonance Imagin...

Multiparametric Ultrasound Imaging of Prostate Cancer Using Deep Neural Networks.

OBJECTIVE: A deep neural network (DNN) was trained to generate a multiparametric ultrasound (mpUS) v...

Super-resolution reconstruction for early cervical cancer magnetic resonance imaging based on deep learning.

This study aims to develop a super-resolution (SR) algorithm tailored specifically for enhancing the...

Artificial intelligence in COPD CT images: identification, staging, and quantitation.

Chronic obstructive pulmonary disease (COPD) stands as a significant global health challenge, with i...

PVTAD: ALZHEIMER'S DISEASE DIAGNOSIS USING PYRAMID VISION TRANSFORMER APPLIED TO WHITE MATTER OF T1-WEIGHTED STRUCTURAL MRI DATA.

Alzheimer's disease (AD) is a neurodegenerative disorder, and timely diagnosis is crucial for early ...

Deep learning-based multimodal spatial transcriptomics analysis for cancer.

The advent of deep learning (DL) and multimodal spatial transcriptomics (ST) has revolutionized canc...

Feasibility of Artificial Intelligence Powered Adverse Event Analysis: Using a Large Language Model to Analyze Microwave Ablation Malfunction Data.

Determine if a large language model (LLM, GPT-4) can label and consolidate and analyze intervention...