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3D MRI Brain Image Segmentation: A Two-Stage Framework

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Book cover Computational Intelligence, Communications, and Business Analytics (CICBA 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 776))

Abstract

Image Segmentation is a process of delineating an image into some meaningful regions. It has the significant impact on the computer guided medical image diagnosis and research. The Magnetic Resonance Imaging (MRI) brain data are severely affected by the noise and inhomogeneity artifacts which lead to blurry edges in the intersection of the intra-organ soft tissue regions. This paper presents a novel two stage framework for segmenting the 3D brain MR image data. The first stage consists of modified fuzzy c-means algorithm (MoFCM) which incorporates the spatial neighborhood information of the volume data to define the new local membership function along with the traditional fuzzy c-means (FCM) membership function. The cluster prototypes obtained from the first stage are fed into the modified spatial fuzzy c-means (MSFCM) algorithm which includes 3D spatial information of the 3D brain MR image volume to generate the final prototypes. Our main endeavor is to address the shortcomings of the traditional FCM which is highly sensitive to noise as it solely depends on the intensity values of the image and develop a new method which performs well in noisy environment. The method is validated on several simulated and in-vivo 3D brain MR image volumes. The empirical results show the supremacy of our method than the other FCM based algorithms devised in the past.

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Acknowledgement

Authors would like to express their profound indebtedness to the EKO X-RAY & IMAGING INSTITUTE, Jawaharlal Neheru Road, Chowrangee, Kolkata, for providing 3D brain MR image data. Authors are thankful to Dr. Amitabha Bhattacharyya for his invaluable suggestion and ardent support.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Jadavpur University, Kolkata, India

    Sayan Kahali & Jamuna Kanta Sing

  2. Department of Computer Science and Engineering, Cooch Behar Government Engineering College, Cooch Behar, India

    Sudip Kumar Adhikari

Authors
  1. Sayan Kahali
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  2. Sudip Kumar Adhikari
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  3. Jamuna Kanta Sing
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Corresponding author

Correspondence to Jamuna Kanta Sing .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Kalyani, Kalyani, West Bengal, India

    J. K. Mandal

  2. Department of Computer and System Sciences, Visva Bharati University, Bolpur Santiniketan, West Bengal, India

    Paramartha Dutta

  3. Department of Information Technology, Calcutta Business School, Kolkata, India

    Somnath Mukhopadhyay

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Kahali, S., Adhikari, S.K., Sing, J.K. (2017). 3D MRI Brain Image Segmentation: A Two-Stage Framework. In: Mandal, J., Dutta, P., Mukhopadhyay, S. (eds) Computational Intelligence, Communications, and Business Analytics. CICBA 2017. Communications in Computer and Information Science, vol 776. Springer, Singapore. https://doi.org/10.1007/978-981-10-6430-2_25

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  • DOI: https://doi.org/10.1007/978-981-10-6430-2_25

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6429-6

  • Online ISBN: 978-981-10-6430-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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