Method for partitioning two-dimensional sequence medical image based on prior knowledge earth-measuring geometry flow

Abstract

The invention provides a two-dimensional sequence medical image segmentation method based on prior knowledge geodesic geometric flow. Firstly, a layer of two-dimensional image is initially segmented by applying Watershed Algorithm and the rough segmentation result of the initial layer is taken as an initial boundary; subsequently, a resegmentation is performed to adjacent layers of images at the upper lower sides respectively from the initial layer layer by layer in a level set method; wherein, the resegmentation result of each layer is taken as the initial boundary of the next layer and the gradient prior knowledge information is provided to the next layer in the form of adjacent layer gradient reference term for segmentation layer by layer till all of the layers are segmented; finally, the segmentation results of all the layers are combined. By introducing the prior knowledge of the adjacent layer in an edge detection function to improve the stop condition of curve evolution and introducing geodesic geometric flow by taking interlayer gradient similarity as the prior knowledge, the method improves the phenomena of edge leakage when a geometric active contour model is opposite to the discontinuous edge or weak edge in the layers and enhances the precision and stability of three-dimensional medical image segmentation.

Description

(1) Technical field [0001] The invention relates to the field of medical image segmentation, in particular to an efficient three-dimensional medical image segmentation method. (2) Background technology [0002] In medical image processing and analysis applications, image segmentation technology plays a key role. The task of medical image segmentation is to extract the region of interest (Region of Interest) containing important diagnostic information from medical images, so as to provide a reliable basis for clinical diagnosis and pathology research. Due to the complexity and difference of the imaging principle of medical images and the structure of human tissue itself, medical images inevitably have the characteristics of blur and inhomogeneity compared with ordinary images; at the same time, the rapid development of medical imaging technology makes various complex images Massive medical image data has become possible, all of which put forward higher requirements for segme...

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Problems solved by technology

But since this term only depends on the gradient information of the image, this external force may still not be enough to completely solve the problem of gap leakage at weak edges of the image

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