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A Novel Curvature Feature Embedded Level Set Method for Image Segmentation of Coronary Angiograms

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Trends and Advances in Information Systems and Technologies (WorldCIST'18 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 746))

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Abstract

Segmentation methods in medical image processing are usually distorted by low contrast and intensity inhomogeneity. There are several image segmentation methods which are based on region based segmentation. But these algorithms mostly depend on the quality of the image. This paper gives an improved level set method for image segmentation to reduce the effect of noise. In order to achieve this, curvature feature energy function in standard level set energy function has been used. The proposed method is being applied on heart angiograms provided by Cardiac Department ISRA University Hospital, Pakistan. Extensive evaluation of these images depicts the robustness and efficiency of the proposed method over the previous work. Moreover, this method gives better trade-off between accuracy and implementation time over the related work.

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Author information

Authors and Affiliations

  1. Mehran University of Engineering and Technology, Jamshoro, Sindh, Pakistan

    Mehboob Khokhar, Shahnawaz Talpur & Rizwan Ali Shah

  2. Institute of Information and Communication Technology, University of Sindh, Jamshoro, Pakistan

    Sunder Ali Khowaja

Authors
  1. Mehboob Khokhar
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  2. Shahnawaz Talpur
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  3. Sunder Ali Khowaja
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  4. Rizwan Ali Shah
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Corresponding author

Correspondence to Shahnawaz Talpur .

Editor information

Editors and Affiliations

  1. Departamento de Engenharia Informática, Universidade de Coimbra, Coimbra, Portugal

    Álvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, Ohio, USA

    Hojjat Adeli

  3. DSI/EEUM, Universidade do Minho, Guimarães, Portugal

    Luís Paulo Reis

  4. DIMES, Universita della Calabria, Arcavacata di Rende, Italy

    Sandra Costanzo

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Khokhar, M., Talpur, S., Khowaja, S.A., Shah, R.A. (2018). A Novel Curvature Feature Embedded Level Set Method for Image Segmentation of Coronary Angiograms. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S. (eds) Trends and Advances in Information Systems and Technologies. WorldCIST'18 2018. Advances in Intelligent Systems and Computing, vol 746. Springer, Cham. https://doi.org/10.1007/978-3-319-77712-2_78

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  • DOI: https://doi.org/10.1007/978-3-319-77712-2_78

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77711-5

  • Online ISBN: 978-3-319-77712-2

  • eBook Packages: EngineeringEngineering (R0)

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