‘’A RESEARCH ON ENCEPHALON CANCER SUBDIVISION: A REVIEW’’

DR. STEPHEN CHARLS

VOLUME02ISSUE11

ABSRACT

Radiography is a method that is drastically used to create pick of human body for medical and lookup purposes. Magnetic Resonance Imaging (MRI) is a powerful visualization device that permits to accumulate picks of interior anatomy of human body in a tightly closed and non-invasive manner. Automatic Encephalon cancer detection from MRI pix has become one of the essential areas of clinical research. The vital mission in the analysis of Encephalon cancer is to decide the exact location, orientation and location of the atypical tissues. These papers discuss the performance analysis of photograph subdivision techniques, viz., K-Means Clustering, Fuzzy C-Means Clustering and Region Growing for detection of Genius cancer from sample MRI pictures of Encephalon. The overall performance contrast of the above stated techniques is executed on the foundation of error share as in contrast to ground truth.

KEYWORDS

Radiography;, intelligence cancer subdivision, region growing, clustering.

REFERENCES

1 M.K., International Agency for Research on Cancer, France, 2010

2 http://globocan.iarc.fr

3 Dr. Jhon L. , National Conference on Computing and Communication Systems (NCCCS)2011

4 Divya Choube, International Conference on Computational Intelligence and Computing Research (ICCIC) 2010.

5. Dr. H.V. ,International Journal of Engineering Science and Technology 2009

AUTHOR’S AFFILIATION

DR. STEPHEN CHARLS
Department Of Life Science, École Normale Supérieure de Lyon Lyon Cedex 07, France.

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