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Information Journal Paper

Title

A PARALLEL IMPLEMENTATION OF MODIFIED FUZZY LOGIC FOR BREAST CANCER DETECTION

Pages

  139-148

Abstract

 According to world health organization, BREAST CANCER is one of the most deadly cancers occurred in women. Therefore accurate diagnosis and prediction is important to decrease the high death rate. The aim of this paper is twofold. First, improving BREAST CANCER detection accuracy using Modified FUZZY LOGIC (MFL) then improving the performance of MFL algorithm using GPU platform. The experimental results show that the accuracy of the BREAST CANCER detection using MFL is higher than other techniques. In addition, by exploiting loop-level parallelism and pipeline parallel communication pattern in MFL algorithm, its performance is improved up to 19.17x for different image sizes.

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    APA: Copy

    HOSEINI, FARNAZ, SHAHBAHRAMI, ASADOLLAH, YAGHOOBI NOTASH, ANARAM, & BAYAT, PEYMAN. (2016). A PARALLEL IMPLEMENTATION OF MODIFIED FUZZY LOGIC FOR BREAST CANCER DETECTION. JOURNAL OF ADVANCES IN COMPUTER RESEARCH, 7(2 (24)), 139-148. SID. https://sid.ir/paper/328837/en

    Vancouver: Copy

    HOSEINI FARNAZ, SHAHBAHRAMI ASADOLLAH, YAGHOOBI NOTASH ANARAM, BAYAT PEYMAN. A PARALLEL IMPLEMENTATION OF MODIFIED FUZZY LOGIC FOR BREAST CANCER DETECTION. JOURNAL OF ADVANCES IN COMPUTER RESEARCH[Internet]. 2016;7(2 (24)):139-148. Available from: https://sid.ir/paper/328837/en

    IEEE: Copy

    FARNAZ HOSEINI, ASADOLLAH SHAHBAHRAMI, ANARAM YAGHOOBI NOTASH, and PEYMAN BAYAT, “A PARALLEL IMPLEMENTATION OF MODIFIED FUZZY LOGIC FOR BREAST CANCER DETECTION,” JOURNAL OF ADVANCES IN COMPUTER RESEARCH, vol. 7, no. 2 (24), pp. 139–148, 2016, [Online]. Available: https://sid.ir/paper/328837/en

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