Hematoxylin-eosin staining pathological image hierarchical segmentation method and terminal
A pathological image, hierarchical segmentation technology, applied in the field of image processing, can solve the problems of poor generalization ability, difference, difficult to establish a stable shape model, etc., to achieve the effect of improving speed and accuracy, reducing difficulty, and facilitating segmentation processing.
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Embodiment 1
[0075] Please refer to Figure 1-Figure 12 , Embodiment 1 of the present invention is:
[0076] A method for hierarchical segmentation of hematoxylin-eosin stained pathological images, specifically, comprising the following steps:
[0077] S1. Perform preprocessing and feature selection on the original hematoxylin-eosin stained pathological image in sequence to obtain a feature set;
[0078] like Figure 4 As shown, specifically, step S1 includes:
[0079] The original hematoxylin-eosin stained pathological images were preprocessed by median filtering and Gaussian filtering successively;
[0080] Preferably, a median filter and a Gaussian filter with a window size of 5×5 and a step size of 1 are used;
[0081] Decompose hematoxylin-eosin stained RGB pathological images into three monochrome images of red, green and blue and convert them into grayscale images respectively as alternative features;
[0082] The hematoxylin-eosin stained image segmentation model based on hier...
Embodiment 2
[0115] Please refer to Figure 1-Figure 12 , the second embodiment of the present invention is:
[0116] A terminal for hierarchical segmentation of hematoxylin-eosin stained pathological images, the terminal includes a memory 1, a processor 2, and a computer program stored in the memory 1 and operable on the processor 2, the processor 2. The various steps in Embodiment 1 are realized when the computer program is executed.
[0117] In summary, the present invention provides a method and terminal for hierarchical segmentation of hematoxylin-eosin stained pathological images, through the preprocessing and feature selection of the original hematoxylin-eosin stained pathological images, to obtain color The two-dimensional feature set of intensity information is convenient for subsequent segmentation; further, K-means clustering and naive Bayesian classification are performed on the image, and the image is segmented step by step to obtain a complete nucleus area, narrow the segmen...
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