Cell edge segmentation method and device based on adaptive morphology

Abstract

The invention provides a cell edge segmentation method and device based on adaptive morphology, and the method comprises the steps: carrying out the instance segmentation of a to-be-segmented cell image through a cell segmentation model, and obtaining an initial segmentation result; based on the statistical characteristics of the cells in the initial segmentation result, performing adaptive iterative corrosion processing on the initial segmentation result to obtain an optimal corrosion result corresponding to the to-be-segmented cell image; wherein convolution parameters in the self-adaptive iterative corrosion treatment process can be reduced along with reduction of the difference between the statistical characteristics of the cells in the initial segmentation result and the statistical characteristics of the cells in the current corrosion result, and the statistical characteristics of the cells in the optimal corrosion result are matched with the statistical characteristics of the cells in the initial segmentation result; and performing fine segmentation on the initial segmentation result based on the optimal corrosion result by using a watershed algorithm to obtain a final segmentation result. According to the method, the smooth edge which is more accurate and more in line with the original form of the cell can be segmented, and the accuracy of cell edge segmentation is improved.

Description

technical field [0001] The invention relates to the technical field of medical image processing, in particular to a cell edge segmentation method and device based on adaptive morphology. Background technique [0002] In recent years, Circulating genetically abnormal cells (CACs, Circulating genetically abnormal cells) have been reported to be found in the peripheral blood of patients with non-small cell lung cancer (NSCLC, Non Small Cell Lung Cancer). The detection of CACs in peripheral blood can predict the existence of tumors earlier, and has broad application prospects. At present, the method for detecting CACs is to collect dark field (DF, Dark Field) microscope images of peripheral blood, use the morphological information of CACs, such as shape, size, and based on manual intervention, mark the DF in the microscope images CACs: Count the labeled CACs, and determine the content of CACs in the blood according to the counting results. However, the method of detecting, con...

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a cell edge segmentation method and device based on adaptive morphology, which is used to solve the problem that it is difficult to ensure the precise segmentation of cell edges in the prior art, and it is difficult to apply to the segmentation task of CACs cells

Images