Health care images contain a variety of imaging information that has specific features, which can make it challenging to assess and decide on the methods necessitated to safeguard the highly classified visuals from unauthorized exposure during transm...
Traditional medical image sensors face multiple challenges. First, these sensors typically rely on large amounts of labeled data, which are time-consuming and costly to obtain. Second, when the data volume and image size are large, traditional sensor...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Medical image segmentation is a fundamental task in many clinical applications, yet current automated segmentation methods rely heavily on manual annotations, which are inherently subjective and prone to annotation bias. Recently, modeling annotator ...
Recently, Deep Learning (DL) models have shown promising accuracy in analysis of medical images. Alzeheimer Disease (AD), a prevalent form of dementia, uses Magnetic Resonance Imaging (MRI) scans, which is then analysed via DL models. To address the ...
Journal of nuclear medicine technology
Dec 4, 2024
Generative artificial intelligence (AI) text-to-image production could reinforce or amplify gender and ethnicity biases. Several text-to-image generative AI tools are used for producing images that represent the medical imaging professions. White mal...
This study systematically reviews CNN-based medical image classification methods. We surveyed 149 of the latest and most important papers published to date and conducted an in-depth analysis of the methods used therein. Based on the selected literatu...
Annals of anatomy = Anatomischer Anzeiger : official organ of the Anatomische Gesellschaft
Nov 29, 2024
BACKGROUND: Artificial intelligence (AI) is rapidly transforming veterinary diagnostic imaging, offering improved accuracy, speed, and efficiency in analyzing complex anatomical structures. AI-powered systems, including deep learning and convolutiona...
This manuscript delineates the pathway from in-house research on Artificial Intelligence (AI) to the development of a medical device, addressing critical phases including conceptualization, development, validation, and regulatory compliance. Key stag...
Virtual histopathology is an emerging technology in medical imaging that utilizes advanced computational methods to analyze tissue images for more precise disease diagnosis. Traditionally, histopathology relies on manual techniques and expertise, oft...
While deep learning (DL) offers the compelling ability to detect details beyond human vision, its black-box nature makes it prone to misinterpretation. A key problem is algorithmic shortcutting, where DL models inform their predictions with patterns ...
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