Nucleus segmentation method based on white blood cell detection

Abstract

The invention belongs to the field of medical image processing and especially relates to a nucleus segmentation method based on white blood cell detection. The method comprises the following steps: to begin with, summarizing the size of diameter of each kind of white blood cell to set a plurality of sizes of sliding windows; then, selecting a candidate window for each sliding window according to gradient information of each white blood cell picture; calculating characteristic value of each candidate window according to the color contrast information, boundary density contrast information and gradient contrast information of the white blood cell pictures, and inputting the characteristic values to an epsilon-SVR model, and selecting a final detection window; intercepting the region of the final detection window of each white blood cell picture as a final positioning subgraph; and then, selecting threshold segmentation nucleus through a subgraph gray statistical chart polynomial curve fitting method, and then, carrying out hole filling and isolated point removal through morphologic processing to enable the segmentation result to be more accurate.

Description

technical field [0001] The invention belongs to the field of medical image processing, in particular to a cell nucleus segmentation method based on white blood cell detection. Background technique [0002] The automatic white blood cell morphology analysis system has four main steps: preprocessing, segmentation, feature extraction and classification. Many scholars pay more attention to the research of the latter three parts, but do not invest a lot of energy in preprocessing. The preprocessing step includes many aspects, such as cell detection and image enhancement, etc. Good preprocessing can have a great impact on the subsequent segmentation work. The five types of leukocytes have different shapes and sizes, and their staining images are often affected by human subjective factors and objective factors of different characteristics of various types of cells, etc., which may lead to lighter staining of white blood cells or darker staining of red blood cells. And uneven brig...

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Problems solved by technology

These methods have been tried to be used in white blood cell segmentation, the method has advantages and disadvantages, and the effect is not well applicable to white blood cell segmentation

Of course, some people have considered using preprocessing to improve the segmentation effect. Among them, Rezatofighi et al. first used the Gram-Schmidt method to extract the nucleus, and then used the square window centered on the center of the nucleus as the detection window of white blood cells, and then based on the detection window Then apply some mature segmentation methods, but some cell nuclei are often multi-lobed, U-shaped or W-shaped, and the center of the nucleus does not represent the center of the white blood cell, so the white blood cell cannot be accurately detected, which in turn will affect the segmentation result of the white blood cell

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