Brain tumor boundary detection in MR image with generalized fuzzy operator

Boundary detection in MR image with brain tumor is an important image processing technique applied in radiology for 3D reconstruction. The nonhomogeneities density tissue of the brain with tumor can result in achieving the inaccurate location in any boundary detection algorithms. Recently, some studies using the contour deformable model with regional base technique, the performance is insufficient to obtain the fine edge in the tumor, and the considerable error in accuracy is existed. Moreover, even in some of the normal tissue region, edge created by this method has also been encompassed. In this paper, we propose a new approach to detect the boundary of brain tumor based on the generalized fuzzy operator (GFO). One typical example is used for evaluating this method with the contour deformable model.

[1]  Dong Joong Kang Stable snake algorithm for convex tracking of MRI sequences , 1999 .

[2]  Yan Zhu,et al.  Computerized tumor boundary detection using a Hopfield neural network , 1997, IEEE Transactions on Medical Imaging.

[3]  F. K. Lam,et al.  Object boundary location by region and contour deformation , 1996 .

[4]  Tony F. Chan,et al.  Active contours without edges , 2001, IEEE Trans. Image Process..

[5]  Chen Jianjun,et al.  A new algorithm of edge detection for color image: Generalized fuzzy operator , 1995 .

[6]  Esther de Ves,et al.  An active contour model for the automatic detection of the fovea in fluorescein angiographies , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[7]  P. Laguna,et al.  Signal Processing , 2002, Yearbook of Medical Informatics.

[8]  Ioannis Pitas,et al.  Digital Image Processing Algorithms , 1993 .

[9]  Nico Karssemeijer,et al.  Normalization of local contrast in mammograms , 2000, IEEE Transactions on Medical Imaging.