A thresholding method for automatic cell image segmentation. | Zendy

H Borst | Zendy; W. Abmayr | Zendy; P. Gais | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

A thresholding method for automatic cell image segmentation.

Author(s) -

H Borst,

W. Abmayr,

P. Gais

Publication year - 1979

Publication title -

journal of histochemistry and cytochemistry

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.971

H-Index - 124

eISSN - 1551-5044

pISSN - 0022-1554

DOI - 10.1177/27.1.374573

Subject(s) - thresholding , artificial intelligence , histogram , computer vision , image histogram , image segmentation , image (mathematics) , cytoplasm , segmentation , pattern recognition (psychology) , computer science , region growing , scale space segmentation , image texture , biology , microbiology and biotechnology

An algorithm for automatic segmentation of PAP-stained cell images and its digital implementation is described. First, the image is filtered in order to eliminate the granularily and small objects in the image which may upset the segmentation procedure. In a second step, information on gradient and compactness is extracted from the filtered image and stored in three histograms as functions of the extinction. From these histograms, two extinction thresholds are computed. These thresholds are suitable to separate the nucleus from the cytoplasm, and the cytoplasm from the background in the filtered image. Masks are determined in this way, and finally used to analyse the nucleus and the cytoplasm in the original image.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research