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Non-rigid Joint Segmentation and Registration Using Variational Approach for Multi-modal Images

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Progress in Intelligent Decision Science (IDS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1301))

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Abstract

Segmentation and registration are two common problems in medical imaging in particular and computer vision in general. These two problems have been studied substantially in the past two decades and often required as simultaneous tasks. Combination of these tasks in a single framework has proven to yield better results in terms of accuracy. In this paper, a model for the joint segmentation and registration based on the variational approach is presented for non-rigid multi-modal. The model is based on an active contour without edges for the segmentation task, normalized gradient fields, and the linear curvature model for image registration. The discrete functional of the new joint model is optimized using coarse to fine registration. The model is evaluated on synthetic and medical images and compared with the existing model. The proposed model is comparable based on the two evaluation criteria used.

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Acknowledgment

MI would like to acknowledge funding from the Ministry of Higher Education of Malaysia (RACER/1/2019/ICT01/UPNM/1).

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Authors and Affiliations

  1. Centre for Defence Foundation Studies, National Defence University of Malaysia, 57000, Kuala Lumpur, Malaysia

    Mazlinda Ibrahim

  2. Biomedical Engineering Department, Bahcesehir University, Besiktas, Istanbul, Turkey

    Lavdie Rada

  3. Biomedical Engineering Department, Heidelberg University, Heidelberg, Germany

    Adela Ademaj

  4. Centre for Mathematical Imaging Techniques and Department of Mathematical Sciences, The University of Liverpool, Liverpool, L69 7ZL, UK

    Ke Chen

Authors
  1. Mazlinda Ibrahim
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  2. Lavdie Rada
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  3. Adela Ademaj
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  4. Ke Chen
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Corresponding author

Correspondence to Mazlinda Ibrahim .

Editor information

Editors and Affiliations

  1. Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul, Turkey

    Tofigh Allahviranloo

  2. Faculty of Engineering and Natural Sciences, Bahçeşehir University, Istanbul, Turkey

    Soheil Salahshour

  3. Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul, Turkey

    Nafiz Arica

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Ibrahim, M., Rada, L., Ademaj, A., Chen, K. (2021). Non-rigid Joint Segmentation and Registration Using Variational Approach for Multi-modal Images. In: Allahviranloo, T., Salahshour, S., Arica, N. (eds) Progress in Intelligent Decision Science. IDS 2020. Advances in Intelligent Systems and Computing, vol 1301. Springer, Cham. https://doi.org/10.1007/978-3-030-66501-2_8

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