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Enhancement of Brain MR-T1/T2 Images Using Mathematical Morphology

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Information and Communication Technology for Sustainable Development

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 933))

Abstract

Brain tumor is a life-threatening disease with a fast growth rate, which makes its detection a critical task. However, low contrast and high noise content in brain MR images hamper the screening of tumor. Enhancement is therefore done to improve the perceivable features of these images. This paper presents an improved enhancement technique of brain MR-T1/T2 images by employing morphological filters. In this method, a disk-shaped flat structuring element along with top-hat and bottom-hat morphological operators is used. The performance of the filter is validated by incrementing values of contrast improvement index (CII) and peak signal-to-noise ratio (PSNR) parameters indicating a successful enhancement without noise amplification.

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Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, 226028, UP, India

    Anu Arya, Vikrant Bhateja, Mansi Nigam & Anuj Singh Bhadauria

Authors
  1. Anu Arya
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  2. Vikrant Bhateja
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  3. Mansi Nigam
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  4. Anuj Singh Bhadauria
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Corresponding author

Correspondence to Anu Arya .

Editor information

Editors and Affiliations

  1. Singidunum University, Belgrade, Serbia

    Milan Tuba

  2. Department of Electronics and Communication Engineering, ITM University, Gwalior, Madhya Pradesh, India

    Shyam Akashe

  3. Sabar Institute of Technology, Gujarat Technological University, Ahmedabad, Gujarat, India

    Amit Joshi

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Arya, A., Bhateja, V., Nigam, M., Bhadauria, A.S. (2020). Enhancement of Brain MR-T1/T2 Images Using Mathematical Morphology. In: Tuba, M., Akashe, S., Joshi, A. (eds) Information and Communication Technology for Sustainable Development. Advances in Intelligent Systems and Computing, vol 933. Springer, Singapore. https://doi.org/10.1007/978-981-13-7166-0_82

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