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  2. Volume 7, Issue 11
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Online ISSN: 2515-8260

Volume7, Issue11

DETECTION OF MICROCALCIFICATION CLUSTERS USING STATISTICAL PARAMETERS AND DYADIC CONTOURLET TRANSFORM BASED PRECISION ENHANCEMENT

    Venmathi A R A. Senthil Kumar M. Gomati G. Suresh

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 11, Pages 2423-2436

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Abstract

Recent scenario, breast cancer found to be a threat and dangerous carcinoma among women in the world. In contemplation of reducing the breast, cancer-related death needs an efficient computer-aided diagnosis (CAD) system. The discrimination of microcalcification clusters (MCCs) is an important manifestation for the early diagnosis of breast cancer. This paper focuses on the detection of breast cancers cells size below 2mm. To achieve précised enhanced cancer cell region an efficient technique dyadic Counterlet transform (DCTs) in two dimension is proposed. The enhancement of cancer cell region obtained through preserving the boundaries and borders with curvature for a small region.
Keywords:
    breast cancer mammography Microcalcification Clusters Wavelet Transform Dyadic Contourlet transform
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(2022). DETECTION OF MICROCALCIFICATION CLUSTERS USING STATISTICAL PARAMETERS AND DYADIC CONTOURLET TRANSFORM BASED PRECISION ENHANCEMENT. European Journal of Molecular & Clinical Medicine, 7(11), 2423-2436.
Venmathi A R; A. Senthil Kumar; M. Gomati; G. Suresh. "DETECTION OF MICROCALCIFICATION CLUSTERS USING STATISTICAL PARAMETERS AND DYADIC CONTOURLET TRANSFORM BASED PRECISION ENHANCEMENT". European Journal of Molecular & Clinical Medicine, 7, 11, 2022, 2423-2436.
(2022). 'DETECTION OF MICROCALCIFICATION CLUSTERS USING STATISTICAL PARAMETERS AND DYADIC CONTOURLET TRANSFORM BASED PRECISION ENHANCEMENT', European Journal of Molecular & Clinical Medicine, 7(11), pp. 2423-2436.
DETECTION OF MICROCALCIFICATION CLUSTERS USING STATISTICAL PARAMETERS AND DYADIC CONTOURLET TRANSFORM BASED PRECISION ENHANCEMENT. European Journal of Molecular & Clinical Medicine, 2022; 7(11): 2423-2436.
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