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Adherent white blood cell segmentation method based on nucleus-marked watershed transformation

A watershed transformation and leukocyte technology, applied in the field of biomedical engineering, can solve problems such as the segmentation of peripheral blood adherent leukocytes, and achieve the effects of ensuring integrity, shortening time-consuming, and reducing the mis-segmentation rate.

Active Publication Date: 2015-03-04
SHANDONG UNIV
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Problems solved by technology

[0011] The purpose of the present invention is to overcome the deficiencies of the above-mentioned prior art, provide a method for segmenting adherent leukocytes based on nuclear marker watershed transformation, and solve the problem of segmenting adherent leukocytes in peripheral blood

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  • Adherent white blood cell segmentation method based on nucleus-marked watershed transformation
  • Adherent white blood cell segmentation method based on nucleus-marked watershed transformation
  • Adherent white blood cell segmentation method based on nucleus-marked watershed transformation

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Embodiment 1

[0058] Such as figure 1 As shown, the specific implementation process of a peripheral blood adhesion leukocyte image segmentation algorithm based on nuclear markers involved in the present invention is as follows:

[0059] In white blood cell identification, medical experts usually distinguish between white blood cells and red blood cells based on characteristics such as color and shape, and distinguish white blood cell types based on information such as texture and space. In this paper, multiple peripheral blood cells were collected to form a cell bank, and white blood cells were segmented from the perspective of color and space. The characteristics of some color channels in the cell bank image were analyzed, and it was found that white blood cells could be accurately segmented through color space and morphological operations. For the adhesion problem in leukocytes, the improved watershed transformation based on nuclear markers can be used to accurately and stably segment le...

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Abstract

The utility model discloses an adherent white blood cell segmentation method based on nucleus-marked watershed transformation. The adherent white blood cell segmentation method comprises the following steps: firstly inputting original RGB (Red, Green, Blue) images and discovering the generally difficult-to-solve problem of peripheral white blood cells and bone marrow white blood cells in the image processing process; secondly, carrying out HIS (Hue-Saturation-Intensity) and LUV color space and grayscale space conversion on the original images and analyzing the characteristics of each channel component image; thirdly, respectively carrying out threshold value segmentation and image subtraction on components B and grayscale images to obtain white blood cell images containing a part of impurities; fourthly, obtaining a target taking a white blood cell nuclei as a marker through an image enhancement technology; fifthly, carrying out morphological operation and watershed transformation on the white blood cell nuclei and the white blood cell images containing the impurities to remove the impurities, obtain accurate white blood cell images and solve the problem of cell adhesion; finally, cutting the targeted white blood cells, converting the targeted white blood cells into an LUV space, clustering the white blood cell images from the view of space and color and obtaining a white blood cell nucleus.

Description

technical field [0001] The invention belongs to the field of biomedical engineering, and in particular relates to a method for segmenting cohesive leukocytes based on nuclear marker watershed transformation. Background technique [0002] The examination of white blood cells is an important part of clinical examination. Inflammation or other diseases in the body can cause changes in the total number of white blood cells and the percentages of various white blood cells. Therefore, checking the total number of white blood cells and the differential count of white blood cells has become an important method for auxiliary diagnosis. The cell image analysis and recognition system has been researched more in recent years. Its main task is to perform cell segmentation on the collected images through automatic analysis and preprocessing, segment individual cells, calculate the relevant characteristic parameters of individual cells, and identify and count the number of different cells. ...

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Application Information

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IPC IPC(8): G06T7/00
CPCG06T7/00G06T7/11G06T2207/20152G06T2207/30024
Inventor 刘治郑成云刘晶马玲李晓梅肖晓燕
Owner SHANDONG UNIV
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