Definition circle HSV color space based medical image segmentation method and cancer cell identification method

Abstract

The invention provides a definition circle HSV color space based medical image segmentation method and a cancer cell identification method. The specific process comprises: step 1, finding out RGB values and position information of a slice image target color pixel P and a background color pixel Q in an RGB color space; step 2, converting an RGB color space based slice image to the HSV color space to obtain an HSV color space based image; step 3, according to position information of the stored pixel P, taking (H,S) corresponding to the pixel P as circle center coordinates of a definition circle, and setting a radius of the definition circle; according to the position information of the pixel Q, extracting H, S and V values corresponding to the pixel Q, assigning the values to all pixels in the definition circle, and removing a target color; and step 4. converting the HSV color space based slice image subjected to removal of the target color back to the RGB color space, and then segmenting the slice image subjected to removal of the target color. By utilizing the definition circle HSV color space based medical image segmentation method and the cancer cell identification method, an extremely accurate segmentation result can be obtained.

Description

technical field [0001] The invention belongs to the technical field of image segmentation, and in particular relates to a medical image segmentation method and a cancer cell identification method based on a defined circular HSV (hue, saturation, illumination) color space. Background technique [0002] Image segmentation is a very widely used technology in the field of image processing, such as video tracking, remote sensing image analysis, medical image analysis, computer vision and other fields will involve image segmentation issues. At present, there are many relatively mature methods in the field of image segmentation. Generally speaking, there are three main entry points for image segmentation: first, the segmentation method based on the gray level of the image target; and second, the segmentation method based on the topology of the image target; The last is the segmentation method based on the image target color. [0003] The classic algorithm based on the target gray ...

AI Technical Summary

Problems solved by technology

But often these segmentation methods for HSV space still have certain errors, because this type of method is only for the image segmentation of the "H" channel, and does not consider the saturation and illumination values ​​"S" and "V". channel effect

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