Abstract
This paper studies the data segmentation of medical images based on compressed sensing. We do not use image data as interpolation data, but as constraints to construct surface patches with quadratic polynomial approximation accuracy, study the properties and correlation of pixels, and take these edge points as constraints, and map the discrete image data into continuous mathematical functions, so that the continuous function or point data not only has the shape recommended by the image data, but also has a higher segmentation accuracy, and then realize the fine segmentation of images, which provides a new research idea to solve the difficult problems of spatial data representation, and has good theoretical significance and application value.
Published Version
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