Detail publikačního výsledku

Breast Cancer Classification Using Statistical Features and Fuzzy Classification of Thermograms

ZÁVIŠEK, M.; DRASTICH, A.

Originální název

Breast Cancer Classification Using Statistical Features and Fuzzy Classification of Thermograms

Anglický název

Breast Cancer Classification Using Statistical Features and Fuzzy Classification of Thermograms

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

Advances in camera technologies and reduced equipment costs have lead to an increased interest in the application of thermography in the medical fields. Thermography is of particular interest for detection of breast cancer as it has been shown that it is capable of detecting the cancer earlier and is also allows diagnosis of fatty breast tissue. In this paper we perform breast cancer detection based on thermography, using a series of statistical features extracted from the thermograms coupled with a fuzzy rule-based classification system for diagnosis. The features stem from a comparison of left and right breast areas and quantify the bilateral differences encountered. Following this asymmetry analysis the features are fed to a fuzzy classification system. This classifier is used to extract fuzzy if-then rules based on a training set of known cases. Experimental results on a set of nearly 150 cases show the proposed system to work well accurately classifying about 80% of cases, a performance that is comparable to other imaging modalities such as mammography.

Anglický abstrakt

Advances in camera technologies and reduced equipment costs have lead to an increased interest in the application of thermography in the medical fields. Thermography is of particular interest for detection of breast cancer as it has been shown that it is capable of detecting the cancer earlier and is also allows diagnosis of fatty breast tissue. In this paper we perform breast cancer detection based on thermography, using a series of statistical features extracted from the thermograms coupled with a fuzzy rule-based classification system for diagnosis. The features stem from a comparison of left and right breast areas and quantify the bilateral differences encountered. Following this asymmetry analysis the features are fed to a fuzzy classification system. This classifier is used to extract fuzzy if-then rules based on a training set of known cases. Experimental results on a set of nearly 150 cases show the proposed system to work well accurately classifying about 80% of cases, a performance that is comparable to other imaging modalities such as mammography.

Klíčová slova

Breast Cancer Classification Statistical Features Fuzzy Thermograms

Klíčová slova v angličtině

Breast Cancer Classification Statistical Features Fuzzy Thermograms

Autoři

ZÁVIŠEK, M.; DRASTICH, A.

Vydáno

26.07.2007

Nakladatel

IEEE

Místo

London UK

ISBN

1-4244-1210-2

Kniha

FUZZ-IEEE 2007 PROCEEDINGS

Strany od

1

Strany do

5

Strany počet

400

URL

http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?isnumber=4295329&arnumber=4295520&count=355&index=190

BibTex

@inproceedings{BUT23027,
  author="Michal {Závišek} and Aleš {Drastich}",
  title="Breast Cancer Classification Using Statistical Features and Fuzzy Classification of Thermograms",
  booktitle="FUZZ-IEEE 2007 PROCEEDINGS",
  year="2007",
  pages="1--5",
  publisher="IEEE",
  address="London UK",
  isbn="1-4244-1210-2",
  url="http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?isnumber=4295329&arnumber=4295520&count=355&index=190"
}