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Breast Cancer Mass Detection in Mammograms Using Gray Difference Weight and MSER Detector

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Abstract

Breast cancer is a deadly and one of the most prevalent cancers in women across the globe. Mammography is widely used imaging modality for diagnosis and screening of breast cancer. Segmentation of breast region and mass detection are crucial steps in automatic breast cancer detection. Due to the non-uniform distribution of various tissues, it is a challenging task to analyze mammographic images with high accuracy. In this paper, background suppression and pectoral muscle removal are performed using gradient weight map followed by gray difference weight and fast marching method. Enhancement of breast region is performed using contrast limited adaptive histogram equalization (CLAHE) and de-correlation stretch. Detection of breast masses is accomplished by gray difference weight and maximally stable external regions (MSER) detector. Experimentation on Mammographic Image Analysis Society (MIAS) and curated breast imaging subset of digital database for screening mammography (CBIS-DDSM) show that the method proposed performs breast boundary segmentation and mass detection with best accuracies. Mass detection achieved high accuracies of about 97.64% and 94.66% for MIAS and CBIS-DDSM dataset, respectively. The method is simple, robust, less affected to noise, density, shape and size which could provide reasonable support for mammographic analysis.

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Acknowledgements

The authors would like to thank Dr. Deepashree Basavalingu, Consultant Radiologist, Blackpool Teaching Hospitals, NHS Foundation Trust, United Kingdom for her certification of ground truths, valuable help and comments in carrying out this work. The first author would like to thank the Ministry of Tribal Affairs, Government of India for awarding the National Fellowship (201718-NFST-KAR-00159) to carry out this research work.

Funding

The first author would like to thank the Ministry of Tribal Affairs, Government of India for awarding the National Fellowship (201718-NFST-KAR-00159) to carry out this research work.

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  1. Department of Studies in Computer Science, University of Mysore, Manasagangotri, Mysore, Karnataka, 570006, India

    B. V. Divyashree & G. Hemantha Kumar

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  1. B. V. Divyashree
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Correspondence to B. V. Divyashree.

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Divyashree, B.V., Kumar, G.H. Breast Cancer Mass Detection in Mammograms Using Gray Difference Weight and MSER Detector. SN COMPUT. SCI. 2, 63 (2021). https://doi.org/10.1007/s42979-021-00452-8

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