Classification method and system for cancer digital pathological cell image

Abstract

The invention provides a classification method and a classification system for cancer digital pathological cell images. According to the classification method and the classification system, a suspected lesion region of interest is subjected to block processing, the suspected lesion region after block processing is subjected to feature extraction by utilizing partial matching pattern textural features, and the extracted features are classified and identified by adopting an extreme learning machine training method, so as to determine benign and malignant tumors and differentiate levels. The classification method and the classification system for the cancer digital pathological cell images utilize the partial matching pattern textural features for conducting feature extraction, analyze the textural features of cells from macroscopic and microscopic aspects, have the advantage of rotation invariance, effectively overcome the problems of diversity, irregularity and the like of cell morphology, provide reliable textural feature information for classification, apply an extreme learning machine to the classification of breast cancer cells, shorten the training time, accelerate the speed of classification and identification, and improve the accuracy of recognition.

Description

technical field [0001] The invention relates to the technical field of medical image processing, in particular to a method and system for classifying cancer digital pathological cell images. Background technique [0002] Breast cancer is a common malignancy among women in today's society. According to the latest statistics released by the World Health Organization (WHO) in February 2014 in the "World Cancer Report", in 2012, breast cancer was one of the three major cancers in the world (lung cancer, breast cancer, and colorectal cancer), accounting for the proportion of all cancers. 25%, ranking second. Therefore, how to prevent, diagnose and treat breast cancer more effectively, so as to reduce the damage of breast cancer to human beings, has become a very important topic in the medical field today. [0003] Immunohistochemical method has the advantages of high sensitivity and strong specificity, and has been widely used in basic research and clinical examination of patho...

AI Technical Summary

Problems solved by technology

At present, some computer-aided diagnosis methods have been used to improve the sensitivity and specificity of diagnosis. However, due to the differences in the preparation and staining methods of breast cell slices, the complexity of the background, the diversity and irregularity of cell shapes, etc., a large number of sample training is required, so it is impossible to obtain the classification results efficiently in terms of time. As a result, in terms of the accuracy of discrimination, the current method of feature extraction cannot make the classification results have a high accuracy.

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