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Particle method for segmentation of breast tumors in ultrasound images

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  • Karunanayake, N.
  • Aimmanee, P.
  • Lohitvisate, W.
  • Makhanov, S.S.

Abstract

We propose a new segmentation method based on multiple walking particles (WP) bouncing from the image edges. The particles are able to segment objects characterized by deep concavities as narrow as one pixel and handle single or multiple objects characterized by a noisy background and broken boundaries (“weak edge”, “boundary leakage”). The particles are designed to segment the image by permanently staying inside the object and repairing the boundaries where necessary. The proposed WP combine the advantages of the continuous diffusion models with the principles of multi-agent systems.

Suggested Citation

  • Karunanayake, N. & Aimmanee, P. & Lohitvisate, W. & Makhanov, S.S., 2020. "Particle method for segmentation of breast tumors in ultrasound images," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 170(C), pages 257-284.
    • Handle: RePEc:eee:matcom:v:170:y:2020:i:c:p:257-284
    DOI: 10.1016/j.matcom.2019.10.009
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    Cited by:

    1. Cuevas, Erik & Becerra, Héctor & Luque, Alberto, 2021. "Anisotropic diffusion filtering through multi-objective optimization," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 181(C), pages 410-429.
    2. Kumar, Ankit & Majee, Sudeb & Jain, Subit K., 2023. "CDM: A coupled deformable model for image segmentation with speckle noise and severe intensity inhomogeneity," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).

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