Use of cytomorphometry for classification of subcellular patterns in 3D images

Authors

  • Eduardo Henrique Silva 1 - Faculdade de Computação - Universidade Federal de Uberlândia, Uberlândia, MG, Brasil 2 - Centro Universitário de Patos de Minas (UNIPAM), Patos de Minas, MG, Brasil http://orcid.org/0000-0003-0809-135X
  • Jefferson Rodrigo de Souza Faculdade de Computação - Universidade Federal de Uberlândia, Uberlândia, MG, Brasil http://orcid.org/0000-0001-6422-4722
  • Bruno Augusto Nassif Travençolo Faculdade de Computação - Universidade Federal de Uberlândia, Uberlândia, MG, Brasil http://orcid.org/0000-0001-7690-301X

DOI:

https://doi.org/10.22456/2175-2745.80598

Keywords:

Image Processing, Cytomorphometry, HeLa cells, QDA

Abstract

This paper presents a methodology for the classification of subcellular patterns by the extraction of cytomorphometric features in 3D isosurfaces. In order to validate the proposal, we used a database of 3D images of HeLa cells with nine classes. For each cell, several morphological attributes were extracted based on its isosurface. Using the Quadratic Discriminant Analysis (QDA) classifier with the hybrid attribute selector, we achieved 97.59 of accuracy and F1-score of 0.9757 when classifying the subcellular patterns.

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Published

2018-07-17

How to Cite

Silva, E. H., Souza, J. R. de, & Travençolo, B. A. N. (2018). Use of cytomorphometry for classification of subcellular patterns in 3D images. Revista De Informática Teórica E Aplicada, 25(2), 47–55. https://doi.org/10.22456/2175-2745.80598

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Section

Regular Papers