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Brain Tumor and Its Segmentation From Brain MRI Sequences
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Author(s): Sanjay Saxena (International Institute of Information Technology, India), Puspanjali Mohapatra (International Institute of Information Technology, India)and Swati Pattnaik (International Institute of Information Technology, India)
Copyright: 2019
Pages: 22
Source title:
Early Detection of Neurological Disorders Using Machine Learning Systems
Source Author(s)/Editor(s): Sudip Paul (North-Eastern Hill University Shillong, India), Pallab Bhattacharya (National Institute of Pharmaceutical Education and Research (NIPER) Ahmedabad, India)and Arindam Bit (National Institute of Technology Raipur, India)
DOI: 10.4018/978-1-5225-8567-1.ch004
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Abstract
Automated segmentation of tumorous region from the brain magnetic resonance image (MRI) is the procedure of extrication anomalous tissues from regular tissues, such as white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). The process of accurate and efficient segmentation is still exigent because of the diversity of location, size, and shape of the tumorous region. Brain MRI provides metabolic process, psychological process, and descriptive information of the brain. Brain tumor segmentation using MRI is drawing the attention of the researchers due to its non-invasive nature and good soft tissue contrast of MRI sequences. The main motive of this chapter is to provide a broad overview of the methods of brain tumor segmentation based on MRI. This chapter provides the information of the brain tumor, its types, brief introduction of the MRI, and its diverse types, and lastly, this chapter gives the brief overview with benefits and limitations about diverse techniques used for brain tumor segmentation by different researchers and scientists.
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