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Automatic Detection Algorithm of Radiation Surgery Area using Morphological Operation and Average of Brain Tumor Size
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 Title & Authors
Automatic Detection Algorithm of Radiation Surgery Area using Morphological Operation and Average of Brain Tumor Size
Na, S.D.; Lee, G.H.; Kim, M.N.;
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 Abstract
In this paper, we proposed automatic extraction of brain tumor using morphological operation and statistical tumors size in MR images. Neurosurgery have used gamma-knife therapy by MR images. However, the gamma-knife plan systems needs the brain tumor regions, because gamma-ray should intensively radiate to the brain tumor except for normal cells. Therefore, gamma-knife plan systems spend too much time on designating the tumor regions. In order to reduce the time of designation of tumors, we progress the automatical extraction of tumors using proposed method. The proposed method consist of two steps. First, the information of skull at MRI slices remove using statistical tumors size. Second, the ROI is extracted by tumor feature and average of tumors size. The detection of tumor is progressed using proposed and threshold method. Moreover, in order to compare the effeminacy of proposed method, we compared snap-shot and results of proposed method.
 Keywords
MRI;Detection;Meningioma;Tumor;
 Language
Korean
 Cited by
 References
1.
E.J. Choi, H.W. Ro, J.S. Cho, M.H. Park, J.H. Yoon, and Y.J. Jegal, “Gamma Knife Surgery for Brain Metastases from Breast Carcinoma,” Journal of the Korean Surgical Society, Vol. 76, No. 2, pp. 81-85, 2009. crossref(new window)

2.
S.D Chang, W. Main, D.P. Martin, I.C. Gibbs, and M. Peter, “An Analysis of the Accuracy of the CyberKnife: A Robotic Frameless Stereotactic Radiosurgical System,” Journal of Neurosurgery, Vol. 52, No. 1, pp. 140-147, 2003.

3.
L. Cozzi, K.A. Dinshaw, S.K. Shrivastava, U. Mahantshetty, D.D. Deshpande, S.V. Jamema, et. al., “A Treatment Planning Study Comparing Volumetric Arc Modulation with RapidArc and Fixed Field IMRT for Cervix Uteri Radiotherapy,” Journal of Radiotherapy and Oncology, Vol. 89, Issue 2, pp. 180-191, 2008. crossref(new window)

4.
R.F. Young, “Gamma Knife Radiosurgery for Treatment of Trigeminal Neuralgia: Idiopathic and Tumor Related,” Journal of Neurology, Vol. 48, Issue 3, pp. 608, 1997. crossref(new window)

5.
J.J. Battermann, K. Breur, G.A.M. Hart, and H.A.V. Peperzeel, “Observations on Pulmonary Metastases in Patients after Single Doses and Multiple Fractions of Fast Neutrons and Cobalt-60 Gamma Rays,” European Journal of Cancer, Vol. 17, Issue 5, pp. 539-548, 1981. crossref(new window)

6.
J.Y.C. Cheung, K.N. Yu, C.P. Yu, and R.T.K. Ho, “Monte Carlo Calculation of Single-beam Dose Profiles Used in a Gamma Knife Treatment Planning System,” Journal of Medical Physics, Vol. 25, No. 9, pp. 1673-1675, 1998. crossref(new window)

7.
C.H. Won, D.H. Kim, J.H. Lee, S.H. Woo, and J.H. Cho, “Segementation of Brain Ventricle using geodesic Active Contour Model based on Region Mean,” Journal of Korean Multimedia Sosicty, Vol. 9, No. 9, pp. 1150-1159, 2006.

8.
Gonzalez. Wood, Digital image Processing Using MATLAB, Prentice-Hall, New jersey, 2004.

9.
K.H. Lee, “Tumor Boundary Extraction in MR Brain Image using Erosion and Region Growing,” Proceeding of Korea Multimedia Sosiety, pp. 849-852, 2006.