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Multimedia Tools and Applications

, Volume 78, Issue 14, pp 20239–20262 | Cite as

Detection of breast cancer mass using MSER detector and features matching

  • Shayma’a A. HassanEmail author
  • Mohammed S. Sayed
  • Mahmoud I. Abdalla
  • Mohsen A. Rashwan
Article
  • 124 Downloads

Abstract

Detection of breast cancer masses in mammogram images is an essential step in any computer-aided system for breast cancer diagnosis. In this paper, we propose a novel technique for breast cancer masses detection in mammograms based on the feature matching of different regions using Maximally Stable Extremal Regions (MSER). Firstly, a pre-processing step is applied to the original mammogram image to produce an enhanced version of this image. Then, MSER regions are extracted from both the original image and its enhanced version using MSER detector. Finally, feature matching process is applied between these regions to detect the mass area. The proposed algorithm has been tested on a collected set of 300 mammogram images containing abnormalities (i.e. benign and malignant masses) from four different databases. The proposed algorithm is able to accurately detect locations of masses with an accuracy of 95%. There aren’t any processing steps for pectoral muscle removal, this results in reducing the processing time. The average time taken by the proposed method to process one mammogram image is 0.14 s. The proposed method is fully automated and there is no need for user intervention or any readjustment. The proposed algorithm is robust against noise and it is not affected by the image quality, breast density category, or mass nature. The results show that the proposed algorithm has higher accuracy than the state of the art approaches.

Keywords

Mammogram images Computer-aided diagnosis MSER regions Feature matching 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Electronics and Communications EngineeringZagazig UniversityZagazigEgypt
  2. 2.Department of Electronics and Communications EngineeringEgypt-Japan University of Science and TechnologyNew Borg El-Arab CityEgypt
  3. 3.Department of Electronics and Communications EngineeringCairo UniversityCairoEgypt

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