• DocumentCode
    250012
  • Title

    Mammography Feature Analysis and Mass Detection in Breast Cancer Images

  • Author

    Patel, Bhagwati Charan ; Sinha, G.R.

  • Author_Institution
    Dept. of Inf. Technol., Shri Shankaracharya Group of Instn., Bhilai, India
  • fYear
    2014
  • fDate
    9-11 Jan. 2014
  • Firstpage
    474
  • Lastpage
    478
  • Abstract
    This paper introduces a novel approach for accomplishing mammographic feature analysis through detection of tumor, in terms of their size and shape with experimental work for early breast tumor detection. The objective is to detect the abnormal tumor/tissue inside breast tissues using three stages: Preprocessing, Segmentation and post processing stage. By using preprocessing noise are remove and than segmentation is applied to detect the mass, after that post processing is applied to find out the benign and malignant tissue with the affected area in the cancers breast image. Size of tumor is also detected in these steps. The occurrences of cancer nodules are identified clearly. Compared with an expert observer reading the Mammography, our algorithm achieves 96.5% sensitivity, 89% specificity, 95.6% accuracy value.
  • Keywords
    biological organs; cancer; feature extraction; image denoising; image segmentation; mammography; medical image processing; tumours; accuracy; benign tissue; breast cancer images; image post processing; image preprocessing; image segmentation; malignant tissue; mammography feature analysis; mass detection; noise removal; sensitivity; specificity; tumor detection; Accuracy; Breast cancer; Feature extraction; Image segmentation; Lesions; accuracy; breast cancer; mammography image; segmentation; sensitivity; specificity; tumor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Systems, Signal Processing and Computing Technologies (ICESC), 2014 International Conference on
  • Conference_Location
    Nagpur
  • Type

    conf

  • DOI
    10.1109/ICESC.2014.89
  • Filename
    6745425