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.
The main goal of MIC is to extract clinically relevant information or knowledge from medical images. While closely related to the field of medical imaging, MIC focuses on the computational analysis of the images, not their acquisition. The methods can be grouped into several broad categories: image segmentation, image registration, image-based physiological modeling, and others.[1]
- ^ Perera Molligoda Arachchige, Arosh S.; Svet, Afanasy (2021-09-10). "Integrating artificial intelligence into radiology practice: undergraduate students' perspective". European Journal of Nuclear Medicine and Molecular Imaging. 48 (13): 4133–4135. doi:10.1007/s00259-021-05558-y. ISSN 1619-7089. PMID 34505175. S2CID 237459138.