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As used herein, "medical image computing" or "medical image processing" refers to systems, software, hardware, components, and/or apparatus that involve and combine the fields of computer science, information engineering, electrical engineering, physics, mathematics and medicine. Medical image computing develops computational and mathematical methods for working with medical images and their use for biomedical research and clinical care. One goal for medical image computing is to extract clinically relevant information or knowledge from medical images. While closely related to the field of medical imaging, medical image computing 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. (Search "medical image computing" on Wikipedia.com June 24, 2021. CC-BY-SA 3.0 Modified. Accessed June 24, 2021.) Medical image computing may include one or more processors or controllers on one or more computing devices. Such processors or controllers may be referred to herein as medical image processors. Medical imaging and medical image computing together can provide systems and methods to image, quantify and fuse both structural and functional information about a patient in vivo. These two technologies include the transformation of computational models to represent specific subjects/patients, thus paving the way for personalized computational models. Individualization of generic computational models through imaging can be realized in three complementary directions: definition of the subject-specific computational domain (anatomy) and related subdomains (tissue types); definition of boundary and initial conditions from (dynamic and/or functional) imaging; and characterization of structural and functional tissue properties. Medical imaging and medical image computing enable in the translation of models to the clinical setting with both diagnostic and therapeutic applications. (Id.) In certain embodiments, medical image computing can be used to generate a bone model, a patient specific model, and/or a patent specific instrument from medical imaging and/or medical imaging data.

Added by DJM 2 2022