A Novel Approach Towards Detection and Identification of Stages of Breast Cancer

  • M. Varalatchoumy
  • M. Ravishankar
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 43)


A robust and efficient CAD system to detect and classify breast cancer at its early stages is an essential requirement of radiologists. This paper proposes a system that detects, classifies and also recognizes the stage of the detected tumor which helps radiologists in reducing false positive predictions. A MRM image is preprocessed using histogram equalization and dynamic thresholding approach. Segmentation of the preprocessed image is carried out using a novel hybrid approach, which is a hybridization of PSO and K-Means clustering. Fourteen textural features are extracted from the segmented region in order to classify the tumor using Artificial Neural Network. If the tumor is classified as malignant then the stage of the tumor is identified using size as a key parameter.


Robust and efficient CAD system Histogram equalization and dynamic thresholding Novel hybrid approach of PSO and K-Means clustering Textural features Artificial neural network Size of tumor 


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Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.Department of Information Science and EngineeringDayananda Sagar College of EngineeringBangaloreIndia
  2. 2.Vidya Vikas Institute of Engineering and TechnologyMysoreIndia

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