Breast cancer classification using statistical features and fuzzy classification of thermograms

Gerald Schaefer*, Tomoharu Nakashima, Michal Závišek, Yasuyuki Yokota, Aleš Drastich, Hisao Ishibuchi

*Corresponding author for this work

    Research output: Chapter in Book/Published conference outputConference publication

    Abstract

    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.

    Original languageEnglish
    Title of host publicationIEEE International Conference on Fuzzy Systems
    PublisherIEEE
    ISBN (Print)1424412102, 9781424412105
    DOIs
    Publication statusPublished - 1 Dec 2007
    Event2007 IEEE International Conference on Fuzzy Systems, FUZZY - London, United Kingdom
    Duration: 23 Jul 200726 Jul 2007

    Conference

    Conference2007 IEEE International Conference on Fuzzy Systems, FUZZY
    Country/TerritoryUnited Kingdom
    CityLondon
    Period23/07/0726/07/07

    Fingerprint

    Dive into the research topics of 'Breast cancer classification using statistical features and fuzzy classification of thermograms'. Together they form a unique fingerprint.

    Cite this