Title :
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
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;
Conference_Titel :
Computer and Information Technology (WCCIT), 2013 World Congress on
Conference_Location :
Sousse
Print_ISBN :
978-1-4799-0460-0
DOI :
10.1109/WCCIT.2013.6618776
