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Abstract
The performance of applying voting to MR segmentation is investigated. Three different segmentation methods (fuzzy c-means, Bayes, and k-nearest neighbour) are used as input to the voting algorithm. Using human expert segmented images as a reference an error rate of 7.1% is obtained when applying voting. When comparing to the other methods it is seen that the results of applying the voting algorithm are slightly improved in terms of the error rate, minimum and maximum error.
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References
J.C. Bezdek, L.O. Hall, and L.P. Clarke: Review of MR image segmentation techniques using pattern recognition. Medical Physics, 20(4):1033–1048, 1993.
M. Bro-Nielsen and S. Cotin: Real-time Volumetric Deformable Models for Surgery Simulation using Finite Elements and Condensation. Institute of Mathematical Modelling, Technical University, Denmark, 1995.
L. P. Clarke, R. P. Velthuizen, M. A. Camacho, J. J. Heine, M. Vaidyanathan, L. O. Hall, R. W. Thatcher, and M. L. Silbiger: MRI Segmentation: Methods and Applications. Magnetic Resonance Imaging, 13(3):343–368, 1995.
R.O. Duda and P.E. Hart: Pattern Classification and Scene Analysis. Wiley-Interscience, 1973.
P.T.English and C. Moore: MRI for Radiographers. Springer-Verlag, 1995.
U. Kuhn, Kühnapfel, H.-G. Krumm, and B. Neisius: The Karlsruhe Endoscopic Surgery Trainer-A “Virtual Reality” based Training System for Minimal Invasive Surgery. CAR, 1996.
L. Lam and C.Y. Suen: Application of Majority Voting to Pattern recognition: An Analysis of its Behaviour and Performance. IEEE Transactions on Systems, Man, and Cyberbetics,27(5):553–568, 1997.
B. Parhami: Voting Algorithms. IEEE Transactions on Reliability, 43(4):617–629, 1994.
A. Pommert, M. Riemer, T. Schiemann, R. Schubert, U. Tiede, and K.H. Höhne: Three-Dimensional Imaging in Medicine: Methods and Applications. In Computer-Integrated Surgery, pages 155–174. The MIT Press, 1996.
M. Vaidyanathan, L.P. Clarke, C. Heidtman, R.P. Velthuizen, and L.O. Hall: Normal Brain Volume Measurement using Multispectral MRI Segmentation. Magnetic Resonance Imaging, 15(1):87–97, 1997.
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Dept. of Medical Informatics and Image Analysis, Aalborg University, Fredrik Bajers Vej 7D, 9220, Aalborg, Denmark
Lasse Riis Østergaard & Ole Vilhelm Larsen
- Lasse Riis Østergaard
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- Ole Vilhelm Larsen
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© 1998 Springer-Verlag Berlin Heidelberg
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Østergaard, L.R., Larsen, O.V. (1998). Applying voting to segmentation of MR images. In: Amin, A., Dori, D., Pudil, P., Freeman, H. (eds) Advances in Pattern Recognition. SSPR /SPR 1998. Lecture Notes in Computer Science, vol 1451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0033304
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