Automatic Segmentation in Breast Cancer Using Watershed Algorithm

Hanan Alshanbari, Saad Amin, James Shuttleworth, K. Slman, S. Muslam

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    Accurate and reproducible delineation of breast lesions can be challenging, as the lesions may have complicated topological structures and heterogeneous intensity distributions. Diagnosis using magnetic resonance imaging (MRI) with an appropriate automatic segmentation algorithm can be a better imaging technique for the early detection of malignant breast tumours. The main objective of this system is to develop a method for automatic segmentation and the early detection of breast cancer based on the application of the watershed transform to MRI images. The algorithm was separated into three major sections: pre-processing, watershed and post-processing. After computing different segments, the final image was cleared of all noise and superimposed on the original MRI image to generate the final modified image. The algorithm successfully resulted in the automatic segmentation of the MRI images, and this can be a beneficial tool for the early detection of breast cancer. This study showed that the automatic results correctly agree with manual detection.
    Original languageEnglish
    JournalInternational Journal of Biomedical Engineering and Science
    Issue number2
    Publication statusPublished - Apr 2015

    Bibliographical note

    Creative Commons Attribution License


    • Image Processing
    • Automatic Segmentation
    • Watershed Segmentation
    • Breast Cancer& MRI


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