基于HSV的乳腺癌细胞识别方法

乳腺癌是女性致死率最高的疾病之一，严重威胁女性的身体健康。目前，病理医生判断病症等级，仍通过观察病理切片中的增殖细胞个数，具有很大的主观性。本文提出了一种将RGB彩色空间和HSV彩色空间模型结合的方法，采用各分量的色度特征，通过量化分析建立色度特征方程，实现从病理图像中检测识别乳腺癌增殖细胞。经20组乳腺癌病理切片图像验证，准确性达到了94.2%,优于单色彩空间模型方法约4%,本文提出方法能够更精确识别乳腺癌细胞，为乳腺癌细胞识别提供了一种新方法。

HSV-based breast cancer cell recognition method

Breast cancer is one of the most deadly diseases in women and poses a serious threat to their health.At present,pathologists still judge the disease grade by observing the number of proliferating cells in pathological sections, which is highly subjective.In this paper,we propose a method that combines RGB color space and HSV color space models,uses the chromaticity features of each component,and establishes the chromaticity feature equation by quantitative analysis to achieve the detection and identification of breast cancer proliferating cells from pathological images. The accuracy reaches 94.2%,which is better than the single color space model method by about 4%.The proposed method can identify breast cancer cells more accurately and provides a new method for breast cancer cell identification.