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Machine Intelligence and Signal Analysis pp 485–495Cite as

An Efficient Brain Tumor Detection and Segmentation in MRI Using Parameter-Free Clustering

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 748))

Abstract

Automation in detecting and segmenting brain tumor is the need of the era in order to diagnose human brain magnetic resonance images (MRIs) and required for better treatment planning as compared to the manual process. Manual diagnosis of brain tumor MRI is a time-consuming process and often depends on the expertise of the clinician or radiologist which may lead to a chance of human error. However, automatic brain tumor detection has been a complex task in medical image analysis due to unknown, unstructured nature of abnormality and a huge variability in shape, location, and characteristics of different sub-compartments of the tumor. In this paper, we propose a fully automatic model for brain tumor detection based on parameter-free clustering algorithm and morphological dilation and hole-filling operations. The method is applied to an axial slice of the T1c modality of BRATS 2015 training dataset. In our experiments, we segmented the tumor from the contrast-enhanced T1-weighted image and compared the results with the available ground truth. Results of tumor segmentation achieved of 75% of the Dice similarity coefficient (DSC) for a tumor core region when compared to the ground truth.

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Authors and Affiliations

  1. National Institute of Technology, Uttarakhand, Srinagar (Garhwal), India

    Shiv Naresh Shivhare, Shikhar Sharma & Navjot Singh

Authors
  1. Shiv Naresh Shivhare
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  2. Shikhar Sharma
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  3. Navjot Singh
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Corresponding author

Correspondence to Shiv Naresh Shivhare .

Editor information

Editors and Affiliations

  1. Discipline of Mathematics, Indian Institute of Technology Indore, Simrol, Madhya Pradesh, India

    M. Tanveer

  2. Discipline of Electrical Engineering, Indian Institute of Technology Indore, Simrol, Madhya Pradesh, India

    Ram Bilas Pachori

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Shivhare, S.N., Sharma, S., Singh, N. (2019). An Efficient Brain Tumor Detection and Segmentation in MRI Using Parameter-Free Clustering. In: Tanveer, M., Pachori, R. (eds) Machine Intelligence and Signal Analysis. Advances in Intelligent Systems and Computing, vol 748. Springer, Singapore. https://doi.org/10.1007/978-981-13-0923-6_42

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