Uterine neck cell image characteristic identification method and uterine neck cell characteristic identification apparatus

Abstract

The invention provides a uterine neck cell image characteristic identification method and a uterine neck cell characteristic identification apparatus. The uterine neck cell image characteristic identification method comprises the following steps: S100, converting a uterine neck cell color picture into a gray-scale image; S200, segmenting the uterine neck cell grey-scale image by use of a mean value segmentation method to extract nuclei of uterine neck cells; S300, accurately positioning the centers of the nuclei by use of a gray scale weight center positioning method; S400, converting a uterine neck cell image in a cartesian coordinate system into a uterine neck cell image in a polar coordinate system; S500, taking a vector composed of a gray-scale median value of the uterine neck cell image on each polar radius in the polar coordinate system as a characteristic vector of the uterine neck cell image; and S600, training a support vector machine vector machine classifier by use of a uterine neck cell training sample and performing class determination on the image of the uterine neck cell training sample by use of the classifier. Compared to geometrical characteristics extracted by use of a conventional method, the uterine neck cell image characteristic identification method has the advantages of dimension invariability, rotation invariability, high identification rate and fast identification speed.

Description

Technical field [0001] The invention belongs to the field of medical cell image processing, and specifically relates to a cervical cell image feature recognition method and a cervical cell feature recognition device. Background technique [0002] Cervical cancer has become a killer that seriously endangers women’s health and is one of the malignant tumors with the highest incidence. Whether cervical cancer can be diagnosed in the early stage is the key to doctor's treatment. With the increasing advancement of cytological diagnosis technology, cervical cell diagnosis and identification The method has become the main technique to assist physicians in diagnosing cervical cancer. [0003] At present, the cervical cell recognition method usually extracts the morphological, texture, and color features of the cervical cell image in Cartesian coordinate space as the characteristics of identifying cervical cell cancer. However, in this method, the nucleus, cytoplasm, and background of the c...

AI Technical Summary

Problems solved by technology

[0003] At present, cervical cell identification methods usually extract the morphological features, texture features, and color features of cervical cell images in the Cartesian coordinate space as features for identifying cervical cell cancer. However, in this method, the nucleus, cytoplasm, and background of cells are not It is easy to distinguish, resulting in variable size and insufficient stability, so the extracted features are not sufficient, the recognition rate is low, and the calculation amount is large, and the recognition speed is slow

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