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Title |
Segmenting Brain Tumour Cells using FCM Approach |
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Author |
Dhivya and Lenat Sughirdha |
| Citation |
Vol. 26 No. 5 pp. 47-52 |
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Abstract |
Tumour segmentation is a major process in medical image processing. It can be divided as primary and secondary type of tumor. Primary level tumor do not affect the surrounding cells, whereas secondary level tumors affect surrounding tissues and also day activities. Segmenting this type of tumor is important in early stage itself. It is just a process of partitioning image into several non-overlapping regions which are in understandable format. Generally, segmentation of brain MRI consists of GM, WM, Cerebrospinal fluid(CSF) as normal brain tissues and tumor tissues as (solid or active tumor, edema, or necrosis). FCM (fuzzy C- Means) is used in segmentation for incorporating the local spatial information with that of function. It is an automatic and unsupervised method which makes use of priori information given by radiology experts. Manual segmentation of brain MRI is possible but it is time consuming and results are varying of between medical experts. Automatic or Semi-automatic segmentation is done which produce more accurate segmentation comprised of tumor volume, size, location of tumor, grade, edema enhancement, growth. In medical diagnosis, these type of segmenting brain MRI are very helpful for clinicans to discover tissues of tumor from normal brain tissues. This paper gives overview of different methods of FCM used in tumor segmentation. |
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Keywords |
Fuzzy C- Means, Priori Information, Brain MRI, Tumor Segmentation, Medical Image Processing. |
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