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A Brief Review on Brain Tumour Detection and Classifications

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Bio-inspired Neurocomputing

Part of the book series: Studies in Computational Intelligence ((SCI,volume 903))

Abstract

Recognition of unusual pixels in a source brain Magnetic Resonance Image (MRI) remains a difficult activity owing to various similarities with that of surrounding pixels. The presence of brain tumour pixel detection process has been simplified using preprocessing steps before the proposed method starts. The preprocessing steps earns an attempt to enhance the internal pixel regions for improving the brain tumor pixel detection rate. The preprocessing stage may include noise reduction, pixel resolution enhancement, image registration, edge detection methods and artifact detection and reduction. The available techniques in preprocessing stage has different methods for improving the clarity of the source brain MRI image that leads to further processing such as segmentation and classification of tumor images. The proposed work discusses various conventional methods for brain tumour detection and classifications with the limited number of available information.

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Author information

Authors and Affiliations

  1. Electronics and Communication Engineering, SRM Institute of Science and Technology, Ramapuram Campus, Chennai, 600089, India

    K. Sri Sabarimani & R. Arthi

Authors
  1. K. Sri Sabarimani
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  2. R. Arthi
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Corresponding author

Correspondence to K. Sri Sabarimani .

Editor information

Editors and Affiliations

  1. Sikkim Manipal Institute of Technology, Rangpo, Sikkim, India

    Akash Kumar Bhoi

  2. KIIT Deemed to be University, Bhubaneswar, Odisha, India

    Pradeep Kumar Mallick

  3. National Taipei University of Technology, Taipei, Taiwan

    Chuan-Ming Liu

  4. Aurel Vlaicu University of Arad, Arad, Romania

    Valentina E. Balas

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Sri Sabarimani, K., Arthi, R. (2021). A Brief Review on Brain Tumour Detection and Classifications. In: Bhoi, A., Mallick, P., Liu, CM., Balas, V. (eds) Bio-inspired Neurocomputing. Studies in Computational Intelligence, vol 903. Springer, Singapore. https://doi.org/10.1007/978-981-15-5495-7_4

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