Fuzzy Analysis of X-ray images for automated disease examination

Craig Watman, Kim Le

    Research output: A Conference proceeding or a Chapter in BookConference contribution

    1 Citation (Scopus)

    Abstract

    This paper presents the design of a fuzzy decision system for Cancer and Tuberculosis detection based on X-ray lung images. The system is in a tuning stage based on advices from medical experts. With a training set of 40 positive and 10 negative images, the system can classify correctly 42% positive cases with no false negative results. This is a promising result; however the system needs further tuning with additional features and concise examination rules
    Original languageEnglish
    Title of host publicationInternational Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2004
    EditorsMircea Gh Negoita, Robert J Howlett, Lakhmi C Jain
    Place of PublicationGermany
    PublisherSpringer
    Pages491-497
    Number of pages7
    ISBN (Print)9783540232063
    Publication statusPublished - 2004
    EventKnowledge-Based Intelligent Information and Engineering Systems - Wellington, New Zealand
    Duration: 22 Sep 200424 Sep 2004

    Conference

    ConferenceKnowledge-Based Intelligent Information and Engineering Systems
    CountryNew Zealand
    CityWellington
    Period22/09/0424/09/04

    Fingerprint

    Tuning
    X rays

    Cite this

    Watman, C., & Le, K. (2004). Fuzzy Analysis of X-ray images for automated disease examination. In M. G. Negoita, R. J. Howlett, & L. C. Jain (Eds.), International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2004 (pp. 491-497). Germany: Springer.
    Watman, Craig ; Le, Kim. / Fuzzy Analysis of X-ray images for automated disease examination. International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2004. editor / Mircea Gh Negoita ; Robert J Howlett ; Lakhmi C Jain. Germany : Springer, 2004. pp. 491-497
    @inproceedings{c21be98ec5e543ff8f6757fa02d241e7,
    title = "Fuzzy Analysis of X-ray images for automated disease examination",
    abstract = "This paper presents the design of a fuzzy decision system for Cancer and Tuberculosis detection based on X-ray lung images. The system is in a tuning stage based on advices from medical experts. With a training set of 40 positive and 10 negative images, the system can classify correctly 42{\%} positive cases with no false negative results. This is a promising result; however the system needs further tuning with additional features and concise examination rules",
    author = "Craig Watman and Kim Le",
    year = "2004",
    language = "English",
    isbn = "9783540232063",
    pages = "491--497",
    editor = "Negoita, {Mircea Gh} and Howlett, {Robert J} and Jain, {Lakhmi C}",
    booktitle = "International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2004",
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    Watman, C & Le, K 2004, Fuzzy Analysis of X-ray images for automated disease examination. in MG Negoita, RJ Howlett & LC Jain (eds), International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2004. Springer, Germany, pp. 491-497, Knowledge-Based Intelligent Information and Engineering Systems, Wellington, New Zealand, 22/09/04.

    Fuzzy Analysis of X-ray images for automated disease examination. / Watman, Craig; Le, Kim.

    International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2004. ed. / Mircea Gh Negoita; Robert J Howlett; Lakhmi C Jain. Germany : Springer, 2004. p. 491-497.

    Research output: A Conference proceeding or a Chapter in BookConference contribution

    TY - GEN

    T1 - Fuzzy Analysis of X-ray images for automated disease examination

    AU - Watman, Craig

    AU - Le, Kim

    PY - 2004

    Y1 - 2004

    N2 - This paper presents the design of a fuzzy decision system for Cancer and Tuberculosis detection based on X-ray lung images. The system is in a tuning stage based on advices from medical experts. With a training set of 40 positive and 10 negative images, the system can classify correctly 42% positive cases with no false negative results. This is a promising result; however the system needs further tuning with additional features and concise examination rules

    AB - This paper presents the design of a fuzzy decision system for Cancer and Tuberculosis detection based on X-ray lung images. The system is in a tuning stage based on advices from medical experts. With a training set of 40 positive and 10 negative images, the system can classify correctly 42% positive cases with no false negative results. This is a promising result; however the system needs further tuning with additional features and concise examination rules

    M3 - Conference contribution

    SN - 9783540232063

    SP - 491

    EP - 497

    BT - International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2004

    A2 - Negoita, Mircea Gh

    A2 - Howlett, Robert J

    A2 - Jain, Lakhmi C

    PB - Springer

    CY - Germany

    ER -

    Watman C, Le K. Fuzzy Analysis of X-ray images for automated disease examination. In Negoita MG, Howlett RJ, Jain LC, editors, International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2004. Germany: Springer. 2004. p. 491-497