Volume & Issue no: Volume 6, Issue 5, May 2017
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Title: |
A DETAILED STUDY ON MRI BRAIN TUMOR DETECTION AND SEGMENTATION TECHNIQUES |
Author Name: |
Gopinath S, Dr.Somasundareswari D |
Abstract: |
Abstract
In recent days, brain tumor is a serious cause for increasing humanity among people. During the past few decades, the number
of people suffering and fading from brain tumors has been increased to 300 per year. Detecting and classifying the tumor in
Magnetic Resonance Imaging (MRI) is a critical and challenging task in medical image processing. Because, the MRI provides
the detailed information related to anatomical structures and potential abnormal tissues. So, the detection and segmentation of
brain tumor plays an essential role in medical imaging and it helps to find the exact size and location of the tumor. For this
purpose, different image processing techniques are proposed in the existing works. This paper reviews some of the existing
research works related to brain tumor detection and segmentation. The stages involved in the brain tumor segmentation system
are as follows: preprocessing, feature extraction, classification and segmentation. The preprocessing is an initial stage in any
medical image processing applications. In this stage, the unwanted and irrelevant noise in the given image are eliminated.
After that, the features of the filtered image are extracted to detect the edges. Hence, the classification technique is employed to
determine whether the given image is normal or abnormal. If it is an abnormal image, the segmentation technique is applied to
segment the exact portion of the tumor.
Keywords: Brain Tumor, Magnetic Resonance Imaging (MRI), Benign, Malignant, Computer Vision, Filtering,
Tumor Detection, Segmentation and Classification |
Cite this article: |
Gopinath S, Dr.Somasundareswari D , "
A DETAILED STUDY ON MRI BRAIN TUMOR DETECTION AND SEGMENTATION TECHNIQUES" , International Journal of Application or Innovation in Engineering & Management (IJAIEM) ,
Volume 6, Issue 5, May 2017 , pp.
026-033 , ISSN 2319 - 4847.
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