Method for segmenting white blood cell image
An image segmentation and white blood cell technology, applied in image analysis, image enhancement, image data processing, etc., can solve the problems of slow algorithm speed, sensitivity to glitches and noise, and inability to fully realize morphological segmentation of cells. Guaranteed accuracy
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[0032] The present invention will be further described in detail below in conjunction with specific embodiments.
[0033] A white blood cell image segmentation method includes the following steps:
[0034] (1) Extraction of the initial region of interest (ROI):
[0035] ① Take the green component map of the color image of stained white blood cells as the input image.
[0036] ②The input image is reduced in resolution.
[0037] The size of the resolution reduction multiple dRate depends on the median cellSize of the length and width of the smallest cell in the image. In this example, dRate=Round(cellSize / 10), and Round() is the rounding function.
[0038] ③ Count the histogram of the input image after resolution reduction.
[0039] ④ Obtain the gray level Hmax where the nth pixel of the histogram is located;
[0040] n=pRate×(input image length / dRate)×(input image width / dRate), pRate is the ratio of the cell pixel to the entire input image pixel, which can be obtained by prior knowledge.
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