A Contour Estimation Method for Dense Fibroblasts

Abstract

The invention discloses a method for estimating the contour of dense fiber cells, which includes the following steps: S1, acquiring images of dense fiber cells; S2, performing Frangi filtering on the images of dense fiber cells, and obtaining boundary lines of cell parts and cytoplasmic parts through threshold segmentation region, to obtain an image with a partial contour; S3, obtain the contour control points in the image with a partial contour by the shortest distance search method; S4, for the contour control points on the boundary line of the same cell, retain the endpoint and preset the contour control points Step size m, select a contour control point every m contour control points to obtain a fitting point set; S5, use the B-spline approximation curve algorithm to perform curve fitting based on the fitting point set, and use the fitted closed curve as a cell Contour, to complete the contour estimation of dense fibroblasts. The invention solves the problem that the existing algorithm is difficult to obtain the outline of dense fiber cells.

Description

technical field [0001] The invention relates to the field of cell image segmentation, in particular to a method for estimating the contour of dense fiber cells. Background technique [0002] Cells are the basic unit of structure and function of organisms. Researchers use microscopes to obtain cell images, and then use computer image analysis technology to obtain cell contours, so as to conduct cell counting, type identification and parameter measurement, which is helpful for medical clinical diagnosis and medical development. Cell image segmentation has always been one of the hot research directions, and many segmentation algorithms have been produced in academia. T.Bhagya et al. performed three preprocessing methods of dilation erosion and histogram stretching, mean filtering, and median filtering with four different segmentation algorithms, namely Otsu threshold segmentation, watershed segmentation, Canny edge detection and K-means clustering. Combination, each combinatio...

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Problems solved by technology

[0004] Aiming at the above-mentioned deficiencies in the prior art, a method for estimating the contour of dense fibroblasts provided by the present invention solves the problem that existing algorithms are difficult to perform good contour estimation on dense fibroblasts

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