Open AccessMedical Image Segmentation Based on Combination Method
Author(s) -
Yi Liu,
Caiming Zhang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1651/1/012166
Subject(s) - scale space segmentation , image segmentation , computer science , segmentation , artificial intelligence , interpolation (computer graphics) , image (mathematics) , pixel , representation (politics) , quadratic function , segmentation based object categorization , computer vision , pattern recognition (psychology) , mathematics , quadratic equation , geometry , politics , political science , law
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.