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Medical image computing (MIC) is an interdisciplinary field at the intersection of computer science, information engineering, electrical engineering, physics, mathematics and medicine. This field develops computational and mathematical methods for solving problems pertaining to medical images and their use for biomedical research and clinical care.
Medical Image Analysis (MedIA) is a peer-reviewed academic journal which focuses on medical and biological image analysis.The journal publishes papers which contribute to the basic science of analyzing and processing biomedical images acquired through means such as magnetic resonance imaging, ultrasound, computed tomography, nuclear medicine, x-ray, optical and confocal microscopy, among others.
The future development of these technologies is advantageous as it gives a solution to human limitations in medical image processing. [4] Although a highly accurate and fully automated CAD system has yet to be realized, recent advancements in Artificial Intelligence may allow for functioning implementations. [11]
Medical imaging is the technique and process of imaging the interior of a body for clinical analysis and medical intervention, as well as visual representation of the function of some organs or tissues . Medical imaging seeks to reveal internal structures hidden by the skin and bones, as well as to diagnose and treat disease.
Computer-aided detection (CADe), also called computer-aided diagnosis (CADx), are systems that assist doctors in the interpretation of medical images.Imaging techniques in X-ray, MRI, endoscopy, and ultrasound diagnostics yield a great deal of information that the radiologist or other medical professional has to analyze and evaluate comprehensively in a short time.
Medical Image Computing (the "MIC" in MICCAI) is the field of study involving the application of image processing and computer vision to medical imaging.The goals of medical image computing tasks are diverse, but some common examples are computer-aided diagnosis, image segmentation of anatomical structures and/or abnormalities, and the registration or "alignment" of medical images acquired ...
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Udupa has worked in the fields of medical image science, image processing, and physics analysis of medical imaging and medical diagnostic procedures since the 1980s. He is known for his contributions in image processing [2] and its applications in various fields of science, medicine, and engineering. [3]