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Brain MRI Examination with Varied Modality Fusion and Chan-Vese Segmentation

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Book cover Intelligent Data Engineering and Analytics

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1177))

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Abstract

Newly, varied techniques are implemented to improve and mine the apprehensive segment from the brain MRI obtained with diverse modalities. This work executes an image-fusion practice to combine the MRIs of dissimilar modalities, to improve the correctness in the assessment task. A Principle-Component-Analysis (PCA) supported fusion is employed to enhance tumor of brain MRI. This work considers the 2D slices of BRATS-2015 image for the assessment. Later, the segmentation based on Chan-Vese is executed and its performance is evaluated against DRLS. A comparative investigation among tumor section and ground-truth (GT) is implemented and vital picture-likeliness constraints are computed. The result of this work is compared against DWT-PCA procedure accessible in literature, and the experimental results of this technique offered better results, which substantiate the superiority of PCA practice.

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Author information

Authors and Affiliations

  1. Department of Electronics and Instrumentation Engineering, St. Joseph’s College of Engineering, OMR, Chennai, 600119, Tamil Nadu, India

    D. Abirami, N. Shalini & V. Rajinikanth

  2. Department of Computer and Mathematical Sciences, University of Houston, Downtown, TX, 77002, USA

    Hong Lin

  3. Department of Mechanical Engineering, St. Joseph’s College of Engineering, OMR, Chennai, 600119, Tamil Nadu, India

    Vaddi Seshagiri Rao

Authors
  1. D. Abirami
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  2. N. Shalini
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  3. V. Rajinikanth
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  4. Hong Lin
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  5. Vaddi Seshagiri Rao
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Corresponding author

Correspondence to V. Rajinikanth .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, Kalinga Institute Industrial Technology, Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

  2. Department of Informatics, University of Leicester, Leicester, UK

    Yu-Dong Zhang

  3. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  4. School of Management, National Institute of Technology Karnataka, Surathkal, Karnataka, India

    Ritanjali Majhi

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Abirami, D., Shalini, N., Rajinikanth, V., Lin, H., Rao, V.S. (2021). Brain MRI Examination with Varied Modality Fusion and Chan-Vese Segmentation. In: Satapathy, S., Zhang, YD., Bhateja, V., Majhi, R. (eds) Intelligent Data Engineering and Analytics. Advances in Intelligent Systems and Computing, vol 1177. Springer, Singapore. https://doi.org/10.1007/978-981-15-5679-1_65

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