Liver DTI image segmentation method based on active contour model

Abstract

The invention discloses a liver DTI image segmentation method based on an active contour model. The liver DTI image segmentation method based on the active contour model comprises the steps of data collection, preprocessing of a liver DTI image, edge detection of the liver DTI image and liver DTI image segmentation with the combination of an active contour CV model. According to the liver DTI image segmentation method based on the active contour model, a multi-dimensional space formed by segmentation parameters is efficiently searched with a bionic optimization algorithm, the optical segmentation parameter set is found, the problem brought by the sensitivity of the active contour model to noise can be solved, the computing complexity of the active contour model can be greatly lowered, and thus the efficiency of the algorithm can be improved; due to the fact that the active contour model and the bionic optimization algorithm are combined, the contour of a result can be rapidly smoothed, and thus the accuracy of the segmentation result is improved. The active contour model and the bionic optimization algorithm are combined, the advantages of the two algorithms can be effectively utilized, compensation can be made for the defects of each other, and a better-off effect is achieved.

Description

technical field [0001] The invention relates to an image processing method, in particular to a liver DTI image segmentation method based on an active contour model. The DTI--MRI. Background technique [0002] In 1987, Kass, Witkin, and Terzopolous proposed a brand-new image segmentation model that conforms to the principles of human vision - the Parametric Active Contour Model (Parametric Active Contour Model), also known as the Snakes model, and has been successfully applied to various applications of image processing. . The Snakes model proposed by Kass et al. poses a challenge to the hierarchical computing theory with strict order. In the underlying image understanding tasks such as image segmentation, the correct understanding of the underlying events must depend on high-level knowledge. They tried to design an energy function. The energy The local extremum of the function contains the schemes that can be realized by high-level processing, and the selection of a suitab...

AI Technical Summary

Problems solved by technology

[0015] The purpose of the present invention is to solve the technical problems of complex algorithms, low efficiency and low accuracy of segmentation results in the existing methods, and provide a method for liver DTI image segmentation based on active contour model