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Comparative Studies | Digital Signal Processing | India | Volume 6 Issue 11, November 2017 | Rating: 6.7 / 10
Comparative Study of Brain Tumor Detection in MRI Images
Drishti Shishodiya [2] | Shivam Shukla | Akash Soni [2] | Sonali Awadhesh Singh
Abstract: The method of brain tumor segmentation is nothing but the differentiation of different tumor area from Magnetic Resonance (MR) images. There are number of methods already presented for segmentation of brain tumor efficiently. However, its still criti-cal to identify the brain tumor from MR images. The segmentation process is extraction of different tumor tissues such as active, tumor, necrosis, and edema from the normal brain tissues such as white matter (WM), grey matter (GM), as well cerebrospinal fluid (CSF). As per the survey study, the brain tumors most of time detected easily from brain MR image, but required level of ac-curacy, reproducible segmentation, abnormalities classification is not predictable and straightforward. The segmentation of brain tumor is composed of many stages. The manual process of doing the segmentation of brain MR images is very time consumption and tedious task, and hence it is associated with many challenges. Therefore, we need automated segmentation method for brain images. There are many techniques presented to investigate the performance of automated computerized brain tumor detection for the medical analysis purpose. In this review paper, our main goal is to present the review of different brain tumor segmentation methods using the MR images. The different methods for segmentation are studied with their advantages and disadvantages in this paper.
Keywords: brain tumor, Comparative, segmentation, MRI
Edition: Volume 6 Issue 11, November 2017,
Pages: 1142 - 1144