Automatic cell detection and segmentation method based on deep learning and using adaptive ellipse fitting

Abstract

The invention discloses an automatic cell detection and segmentation method based on deep learning and using adaptive ellipse fitting. A deep learning method is used to detect a cell in a pathologic image, an active contour model is used to search an accurate cell contour, and an adaptive ellipse fitting technology is used to segment contours of overlapped cells. According to the method of the invention, large slice images serve as research objects, deep learning is combined with a sliding window, the position of the cell in the image can be found accurately, and the active contour and the adaptive ellipse fitting are combined to effectively segment the overlapped cells. The method can be used to help clinical doctors evaluate cells in the digital pathologic slices in a quantified manner and make clinical diagnosis rapidly and accurately, diagnosis difference between different observers or different time periods of the same observer is reduced, and compared with a present cell detection and segmentation method, the method of the invention is advantageous in the aspects of both accuracy and feasibility.

Description

technical field [0001] The invention relates to an adaptive ellipse fitting cell automatic detection and segmentation method based on deep learning, and belongs to the technical field of image information processing. Background technique [0002] With the generation of digital scanning technology for large slice images and the improvement of scanning efficiency, the digital display and storage of histopathological slides has become realistic and feasible. Higher quality analysis of pathological images is possible with digital technology. Because the characteristics of various cancer cells and tissues can be found from the pathological images of tissue slices, and can be used to assist doctors in diagnosis, but there are still few technical researches on medical image processing, so we study a set of methods for pathological images. Analytical tools are very important. [0003] The purpose of studying computer-aided system (CAD) is not to completely replace doctors, but to ...

AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is to provide an adaptive ellipse fitting cell automatic detection and segmentation method based on deep learning, which overcomes the problem that the existing cell detection and segmentation algorithm cannot deal with the changeable cell shape and scale and cell overlap in the pathological slice image. Higher segmentation accuracy than other methods

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