Classifying medical images is essential in computer-aided diagnosis (CAD). Although the recent success of deep learning in the classification tasks has proven advantages over the traditional feature extraction techniques, it remains challenging due t...
Journal of nuclear medicine technology
Mar 5, 2025
The recent emergence of text-to-image generative artificial intelligence (AI) diffusion models such as DALL-E, Firefly, Stable Diffusion, and Midjourney has been touted with popular hype about the transformative potential in health care. This hype-dr...
Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Feb 27, 2025
The rising global burden of cancer drives increased demands for medical imaging, which is essential throughout cancer care. However, delivering medical imaging presents significant environmental challenges including high energy use, reliance on singl...
Artificial intelligence (AI), particularly deep learning, has demonstrated remarkable performance in medical imaging across a variety of modalities, including X-ray, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, positron emi...
Machine learning has emerged as a crucial tool for medical image analysis, largely due to recent developments in deep artificial neural networks addressing numerous, diverse clinical problems. As with any conceptual tool, the effective use of machine...
Breast cancer is one of the most common types of cancer affecting women worldwide. Artificial intelligence (AI) is transforming breast cancer imaging by enhancing diagnostic capabilities across multiple imaging modalities including mammography, digit...
BACKGROUND: Radiomics and AI have been widely used in breast cancer imaging, but a comprehensive systematic analysis is lacking. Therefore, this study aims to conduct a bibliometrics analysis in this field to discuss its research status and frontier ...
Transfer learning, particularly fine-tuning models pretrained on photographic images to medical images, has proven indispensable for medical image analysis. There are numerous models with distinct architectures pretrained on various datasets using di...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Feb 14, 2025
Semi-supervised learning based on consistency learning offers significant promise for enhancing medical image segmentation. Current approaches use copy-paste as an effective data perturbation technique to facilitate weak-to-strong consistency learnin...
Diagnostic and interventional radiology (Ankara, Turkey)
Feb 10, 2025
PURPOSE: To comprehensively assess Checklist for Artificial Intelligence in Medical Imaging (CLAIM) adherence in medical imaging artificial intelligence (AI) literature by aggregating data from previous systematic and non-systematic reviews.
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