Similarity analysis of histopathology cell structures using fuzzy rough sets

Author

Tabakov, Martin ; Podhorska-Okolow, Marzenna ; Golofit, Piotr ; Pula, Bartosz ; Grzegrzolka, Jedrzej

Author_Institution

Inst. of Inf., Wroclaw Univ. of Technol., Wroclaw, Poland

fYear

2013

fDate

22-24 June 2013

Firstpage

1

Lastpage

6

Abstract

In this article, a method of histopathology image recognition, based on image similarity is presented. The image similarity is interpreted in terms of fuzzy rough sets. Approximations of fuzzy sets are used for investigation how close (in terms of fuzzy rough sets) is a considered histopathology image to a reference image information, which enables HER2 image recognition. The proposed approach was tested over real clinical data of HER-2/neu breast cancer histopathology images.

Keywords

cancer; fuzzy set theory; image recognition; medical image processing; rough set theory; HER-2/neu breast cancer histopathology images; clinical data; fuzzy rough sets; histopathology cell structures similarity analysis; histopathology image recognition; image similarity; reference image information; Approximation methods; Breast cancer; Fuzzy sets; Image color analysis; Marine animals; Rough sets; HER-2/neu biomarker; Histopathology images; breast cancer; fuzzy rough sets; fuzzy t-equivalence; histopathology image analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Information Technology (WCCIT), 2013 World Congress on

Conference_Location

Sousse

Print_ISBN

978-1-4799-0460-0

Type

conf

DOI

10.1109/WCCIT.2013.6618776

Filename

6618776