Watershed-Matching Algorithm: A New Pathway for Brain Tumor Segmentation
Brain tumor detection through Magnetic Resonance Imaging (MRI) is a very challenging task even in today’s modern medical image processing research. To form images of the soft tissue of the human body, surgeons use MRI analysis. They segment the images manually by partitioning into two distinct regions which is erroneous and at the same time, may be time-consuming. So, it is a must be better the MRI images segmentation. This paper outlines a new finding to detect brain tumor for better accuracy than earlier techniques. We segment the tumor area from the MR image and then to find the area of the segmented region, we use another algorithm to match the segmented part with the input image. In addition, the paper concludes with the status checking of the tumor and provides a necessary diagnosis of brain tumor. Lastly, we compare our proposed model with other techniques and get a far better result.
KeywordsArtifacts Brain tumor segmentation Magnetic resonance imaging Sift algorithm Topology Watershed segmentation
Higher Education Quality Enhancement Project (HEQEP), UGC, Bangladesh Department of EEE, KUET, Bangladesh partly supports this work.
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