Radiology

Latest AI and machine learning research in radiology for healthcare professionals.

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Artificial intelligence in radiology - beyond the black box.

BACKGROUND: Artificial intelligence is playing an increasingly important role in radiology. However,...

Deep learning-based PET/MR radiomics for the classification of annualized relapse rate in multiple sclerosis.

Background Annualized Relapse Rate (ARR) is one of the most important indicators of disease progress...

A fully automated micro‑CT deep learning approach for precision preclinical investigation of lung fibrosis progression and response to therapy.

Micro-computed tomography (µCT)-based imaging plays a key role in monitoring disease progression and...

A trial deep learning-based model for four-class histologic classification of colonic tumor from narrow band imaging.

Narrow band imaging (NBI) has been extensively utilized as a diagnostic tool for colorectal neoplast...

Is ultrasound-guided hip aspiration more successful than fluoroscopic-guided aspiration in diagnosing prosthetic joint infection?

: aspiration of total hip arthroplasty (THA) is commonly performed to assist in the diagnosis of pro...

Imaging of early-stage osteoarthritis: the needs and challenges for diagnosis and classification.

In an effort to boost the development of new management strategies for OA, there is currently a shif...

Deep learning referral suggestion and tumour discrimination using explainable artificial intelligence applied to multiparametric MRI.

OBJECTIVES: An appropriate and fast clinical referral suggestion is important for intra-axial mass-l...

Explainable AI in radiology: a white paper of the Italian Society of Medical and Interventional Radiology.

The term Explainable Artificial Intelligence (xAI) groups together the scientific body of knowledge ...

Data infrastructures for AI in medical imaging: a report on the experiences of five EU projects.

Artificial intelligence (AI) is transforming the field of medical imaging and has the potential to b...

Development and validation of a deep learning radiomics nomogram for preoperatively differentiating thymic epithelial tumor histologic subtypes.

OBJECTIVES: Using contrast-enhanced computed tomography (CECT) and deep learning technology to devel...

Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review.

In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of mortality g...

Deep-Stacked Convolutional Neural Networks for Brain Abnormality Classification Based on MRI Images.

An automated diagnosis system is crucial for helping radiologists identify brain abnormalities effic...

Sociodemographic Variables Reporting in Human Radiology Artificial Intelligence Research.

PURPOSE: Artificial intelligence (AI) is rapidly reshaping how radiology is practiced. Its susceptib...

Denoising diffusion probabilistic models for 3D medical image generation.

Recent advances in computer vision have shown promising results in image generation. Diffusion proba...

Global deep learning optimization of chemical exchange saturation transfer magnetic resonance fingerprinting acquisition schedule.

Chemical exchange saturation transfer (CEST) MRI is a promising molecular imaging technique but suff...

18F-FDG PET/CT Image Deep Learning Predicts Colon Cancer Survival.

Colon cancer is a type of cancer that begins in the large intestine. In the process of efficacy eval...

Effective deep learning classification for kidney stone using axial computed tomography (CT) images.

INTRODUCTION: Stone formation in the kidneys is a common disease, and the high rate of recurrence an...

High-Speed On-Site Deep Learning-Based FFR-CT Algorithm: Evaluation Using Invasive Angiography as the Reference Standard.

Estimation of fractional flow reserve from coronary CTA (FFR-CT) is an established method of assess...

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