Cervix uteri single cell image segmentation algorithm

Abstract

The invention discloses a method of a cervix uteri single cell image segmentation algorithm, and includes the steps of: 1) performing preprocessing on a cervix uteri single cell image to enhance a cell boundary; 2) removing a background of the cervix uteri cell image; 3) determining a gray scale gradient of a cell nucleus and cytoplasm along a ray direction; 4) using a stack gray scale difference compensation algorithm to optimize the ray gray scale gradient in the Step 3), and determining an edge map AREM of the cytoplasm and the cell nucleus of the cervix uteri single cell according to the noise-removed cervix uteri single cell image; and 5) applying gradient vector field GVF Snake model evolution to the determined edge map AREM of the cervix uteri single cell image to accurately locate profiles of the cytoplasm and the cell nucleus of the cervix uteri cell. The method simplifies a complex process of a traditional segmentation algorithm, solves the problems that in the traditional segmentation method cells overlap and adhere, dyed color is inconsistent and a background contains impurities, and improves the segmentation accuracy degree and segmentation efficiency of a normal cervix uteri single cell and a cancerous cervix uteri single cell.

Description

technical field [0001] The invention relates to the field of medical cell image processing, in particular to a cervical single-cell image segmentation algorithm based on an adaptive threshold value and a ray gray gradient active contour model. Background technique [0002] Cervical cancer has become one of the malignant tumors with the highest incidence rate, seriously endangering women's health. Because there are no obvious symptoms in the early stage of cervical cancer, the symptoms in the late stage are obvious but it is very difficult to cure. Therefore, early diagnosis of cervical cancer is the key to physician diagnosis and treatment. In modern medicine, cancer therapy through therapeutic cells is a new direction of development. In a type of computer-aided automatic diagnosis system represented by the cervical single-cell image processing system, the accurate segmentation of the nucleus and cytoplasm from the cell image is the basis for subsequent quantitative analys...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a cervical single-cell image segmentation algorithm for the deficiencies in the prior art. The cervical single-cell image segmentation algorithm of this adaptive threshold and ray gray gradient active contour model can avoid cell overlap in traditional segmentation methods Adhesion, inconsistent staining color and impurities in the background can improve the segmentation accuracy and efficiency of normal cervical single cells and cancerous cervical single cells

Images