Literature DB >> 374573

A thresholding method for automatic cell image segmentation.

H Borst, W Abmayr, P Gais.   

Abstract

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.

Mesh:

Year:  1979        PMID: 374573     DOI: 10.1177/27.1.374573

Source DB:  PubMed          Journal:  J Histochem Cytochem        ISSN: 0022-1554            Impact factor:   2.479


  4 in total

1.  Relationship of ploidy and chromatin condensation in the rat liver, moreover a comparison of the nuclear texture in sections and touch preparations.

Authors:  W Romen; A Rüter; K Saito; H Harms; H M Aus
Journal:  Histochemistry       Date:  1980

2.  Detection and classification of thyroid follicular lesions based on nuclear structure from histopathology images.

Authors:  Wei Wang; John A Ozolek; Gustavo K Rohde
Journal:  Cytometry A       Date:  2010-05       Impact factor: 4.355

3.  Automated analysis of time-lapse imaging of nuclear translocation by retrospective strategy and its application to STAT1 in HeLa cells.

Authors:  Fujun Han; Peizhou Liang; Feifei Wang; Lingyun Zeng; Biliang Zhang
Journal:  PLoS One       Date:  2011-11-18       Impact factor: 3.240

Review 4.  A Review of Computational Methods for Cervical Cells Segmentation and Abnormality Classification.

Authors:  Teresa Conceição; Cristiana Braga; Luís Rosado; Maria João M Vasconcelos
Journal:  Int J Mol Sci       Date:  2019-10-15       Impact factor: 5.923

  4 in total

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