A Benign and Malignant Mass Classification Based on Second-Order Statistical Parameters at Different Offset

  • Pravin PalkarEmail author
  • Pankaj Agrawal
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 34)


The objective of this paper is to investigate the classification of masses on digitized screening mammograms as benign or malignant with second-order statistical parameters. Many CAD tools were developed over the past two decades to help radiologists in detecting and diagnosing breast cancer. The proposed method removes and deletes unwanted signs present in the digitized mammogram sample’s background and applies enhancement process to eliminate noise and find the breast region. After that, segmentation phase is performed for automatic mass detection. From detected mass, second-order texture features from gray level co-occurrence matrix (GLCM) are extracted. These extracted parameters for different offset are plotted and based on the relation of direction’s plots; the mass is classified as benign or malignant.


Breast cancer Mammogram Statistical parameters Segmentation GLCM Mass classification 


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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.RTMNUNagpurIndia
  2. 2.G. H. Raisoni Academy of Engineering and TechnologyNagpurIndia

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