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A Study on Image Segmentation in Curvelet Domain Using Snakes and Fractals for Cancer Detection in Mammograms

  • R. Roopa ChandrikaEmail author
  • S. KarthikEmail author
  • N. KarthikeyanEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 898)

Abstract

Breast cancer is one of the common diseases that affect the quality of life in women. To improve the mortality rate, screening procedures are recommended by medical practitioners. The procedure involves detecting and diagnosing the suspected regions. Detecting the suspected regions in the digital mammograms is a challenging task. In this work, multiresolution analysis is done to resolve the curve discontinuities and procedures like fractals and snakules are applied for segmenting the suspected region. The algorithms have been tested on mini-MIAS and observed that snakes have identified the regions better than fractals. Snakes are able to converge within few iterations determining the circumference of the suspected region and also able to differentiate tumorous and non-tumorous regions.

Keywords

Curvelet Fractals Snakes Mammogram Breast cancer 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Information TechnologyMalla Reddy College of Engineering and TechnologyHyderabadIndia
  2. 2.Department of Computer ApplicationsSNS College of Engineering and TechnologyCoimbatoreIndia
  3. 3.Department of Computer ApplicationsSNS College of EngineeringCoimbatoreIndia

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