Author(s): Sunitha S, Santhoshi Sukumaran
Published in: International Journal of Engineering Research & Technology
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Volume/Issue: Vol. 3 - Issue 4 (April- 2014)
Manually detecting and segmenting brain tumors from brain MRI, in cases where a large number of MRI scans are taken for each patient, is tedious and subjected to inter and intra observer detection and segmentation variability. Therefore, there is a need for computer aided brain tumor detection and segmentation from brain MR images to overcome the tedium and observer variability involved in the manual segmentation. A number of methods have been proposed in recent years to fill this gap, but still there is no commonly accepted automated technique for use in clinical floor by clinicians due to accuracy and robustness issues. This paper, presents a review of the methods used for MRI brain tumor segmentation. The review covers imaging modalities, magnetic resonance imaging and methods for noise reduction and segmentation approaches.
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