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Computed Tomography Image Reconstruction Using Fuzzy Complex Diffusion Regularization

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Innovations in Computational Intelligence and Computer Vision

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1189))

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Abstract

Computed tomography (CT) is one of the most efficient clinical diagnostic tools. The main goal of CT is to reproduce an acceptable reconstructed image of an object (either anatomical or functional behavior) with the help of limited set of its projections at different angles. To achieve this goal, one of the most commonly iterative reconstruction algorithm called as maximum likelihood expectation maximization (MLEM) is used. The conventional maximum likelihood (ML) algorithm can achieve quality images in CT. However, it still suffers from the optimal smoothing as the number of iteration increases. This paper presents a novel statistical image reconstruction algorithm for CT, which utilizes a fuzzy nonlinear complex diffusion as a regularization term for noise reduction and edge preservation. A proposed model has been evaluated on two simulates test case phantoms. Qualitative and quantitative analyses indicate that the proposed technique has higher efficiency for computed tomography when compared with the state-of-the-art techniques.

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Author information

Authors and Affiliations

  1. Deenbandhu Chhotu Ram University of Science and Technology, Murthal, 131039, India

    Manju Devi & Sukhdip Singh

  2. Thapar Institute of Engineering and Technology (TIET), Patiala, 147004, India

    Shailendra Tiwari

Authors
  1. Manju Devi
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  2. Sukhdip Singh
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  3. Shailendra Tiwari
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Corresponding author

Correspondence to Shailendra Tiwari .

Editor information

Editors and Affiliations

  1. Department of Computer and Communication Engineering, Manipal University Jaipur, Jaipur, Rajasthan, India

    Manoj Kumar Sharma

  2. Department of Computer and Communication Engineering, Manipal University Jaipur, Jaipur, Rajasthan, India

    Vijaypal Singh Dhaka

  3. Department of Computer Science, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang, Selangor, Malaysia

    Thinagaran Perumal

  4. Department of Information Technology, Techno India College of Technology, Kolkata, West Bengal, India

    Nilanjan Dey

  5. Faculdade de Engenharia da, Universidade do Porto, Porto, Portugal

    João Manuel R. S. Tavares

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Devi, M., Singh, S., Tiwari, S. (2021). Computed Tomography Image Reconstruction Using Fuzzy Complex Diffusion Regularization. In: Sharma, M.K., Dhaka, V.S., Perumal, T., Dey, N., Tavares, J.M.R.S. (eds) Innovations in Computational Intelligence and Computer Vision. Advances in Intelligent Systems and Computing, vol 1189. Springer, Singapore. https://doi.org/10.1007/978-981-15-6067-5_24

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