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Title |
Effective Segmentation of Brain Tumors using N-MSFCM and Modified Fuzzy Level Set Algorithm |
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Author |
Vijayalaxmi Hegde, Basavaraj N Jagadale, and Panchaxri |
| Citation |
Vol. 22 No. 6 pp. 551-561 |
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Abstract |
A brain tumor is a mass of neoplastic cells in the brain which compresses the surrounding tissues and manifests with features of focal neurological deficit or raised intracranial tension or even seizures. Accurate segmentation of brain lesions is an important step in the medical field as it aids in the exact localization of the tumor which helps in determining the prognosis. It also helps to decide the treatment modality. This paper presents a systematic approach to brain tumor segmentation and labeling, which comprises effective pretreatment of denoising with a combination filter, contrast improvement, and a fusion of innovative fuzzy spaces restricted segmentation and improved fuzzy level set segmentation. The effectiveness of this technique is assessed using conventional parameters in comparison to state-of-the-art contemporary segmentation techniques. According to the findings, the new technique surpasses the others and produces better segmentation results. |
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Keywords |
Clustering, Segmentation, MR images. Fuzzy C Means, Level set. |
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