Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India

Research Article

A Study of Mammographic Image Segmentation with its Morphological Operation

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  • @INPROCEEDINGS{10.4108/eai.7-6-2021.2308787,
        author={G  Balanagireddy and J K Periasamy and G  Saritha and M  Sujatha and G  Nirmalapriya},
        title={A Study of Mammographic Image Segmentation with its Morphological Operation},
        proceedings={Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India},
        publisher={EAI},
        proceedings_a={I3CAC},
        year={2021},
        month={6},
        keywords={breast cancer image segmentation and morphological operations},
        doi={10.4108/eai.7-6-2021.2308787}
    }
    
  • G Balanagireddy
    J K Periasamy
    G Saritha
    M Sujatha
    G Nirmalapriya
    Year: 2021
    A Study of Mammographic Image Segmentation with its Morphological Operation
    I3CAC
    EAI
    DOI: 10.4108/eai.7-6-2021.2308787
G Balanagireddy1,*, J K Periasamy2, G Saritha3, M Sujatha4, G Nirmalapriya5
  • 1: Assistant Professor, Department of Electronics and Communication Engineering, PACE Institute of Technology and Sciences, Ongole, Andhra Pradesh, India
  • 2: Associate Professor, Department of Computer Science and Engineering, Sri Sairam Engineering College, Chennai, Tamil Nadu, India
  • 3: Assistant Professor, Department of Electronics and Communication Engineering, Sri Sairam Institute of Technology, Chennai, Tamil Nadu, India
  • 4: Professor, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Vijayawada, Andhra Pradesh, India
  • 5: Professor, Department of Electronics and Communication Engineering, Rajalakshmi Institute of Technology, Chennai, Tamil Nadu, India.
*Contact email: nagireddy.nano@gmail.com

Abstract

The Malign cell extraction and segmentation differentiation from normal cells is widely researched topic. The process of segmentation with single strategy might miss the features leading to increased mortality rate. This work characterizes the different segmentation methods and two simulation tools for mammogram images. The non-feature pixel values are represented by the nearest feature pixel in distance by watershed segmentation. Simulations are performed with ImageJ using Morphological library where binary mammogram images are analysed with connected components and distance based watershed transform. Finally the mammogram image in DICOM format is analysed for segmenting spanning lower and upper threshold with clustering..