Using fuzzy sugeno integral as an aggregation operator of ensemble of fuzzy decision trees in the recognition of HER2 breast cancer histopathology images

Author

Tabakov, Martin ; Podhorska-Okolow, Marzenna ; Zareba, S. ; Pula, Bartosz

Author_Institution

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

fYear

2013

fDate

20-22 Jan. 2013

Firstpage

1

Lastpage

6

Abstract

In this paper a decision making support system based on fuzzy logic is considered. The examined decision problem is related to the problem of recognition of histopathology images with respect to the degree of HER2/neu receptor overexpression. We used fuzzy decision trees, defined over different sets of image features, as separate image classifiers. Then, the corresponding classifiers results were aggregated with the fuzzy Sugeno integral to make final recognition decision. The proposed approach was tested over real clinical data of HER2 breast cancer histopathology images.

Keywords

biomedical optical imaging; cancer; decision making; decision support systems; decision trees; feature extraction; fuzzy logic; fuzzy set theory; image classification; integral equations; medical image processing; HER2 breast cancer histopathology image recognition; HER2 overexpression; aggregation operator; decision making support system; fuzzy Sugeno integral; fuzzy decision tree ensemble; fuzzy logic; human epidermal growth factor receptor 2; image classifiers; image features; neu receptor overexpression; Biomedical imaging; Breast cancer; Classification algorithms; Decision making; Decision trees; Feature extraction; Medical treatment; HER2 breast cancer; fuzzy ID3 algorithm; fuzzy Sugeno integral; fuzzy decision tree; histopathology image processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Medical Applications (ICCMA), 2013 International Conference on

Conference_Location

Sousse

Print_ISBN

978-1-4673-5213-0

Type

conf

DOI

10.1109/ICCMA.2013.6506188

Filename

6506188