The week's pick
Random Articles
Reseach Article
Rigid Point Feature Registration for MRI Brain Images based on Fuzzy Transform
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 71 - Number 4 |
| Year of Publication: 2013 |
| Authors: Nemir A. Al-azzawi |
10.5120/12343-8626
|
Nemir A. Al-azzawi . Rigid Point Feature Registration for MRI Brain Images based on Fuzzy Transform. International Journal of Computer Applications. 71, 4 ( June 2013), 1-6. DOI=10.5120/12343-8626
Abstract
Radiological images are gradually more being used in healthcare and medical research. There is, accordingly, widespread interest in accurately relating information in the different images for diagnosis, treatment and basic science. In this paper we formulate feature registration problems by using F-transform (Fuzzy-Transform) to extract the salient edges and extracted control points (CP) of medical Images. The MRI brain Images were first decomposed using F-transform, then Edge and CP were extracted from F-transform error function, and some proposed rules. After edge and CP extraction, mutual information (MI) was adopted for the registration of feature points, and translation parameters are calculated by using particle swarm optimization (PSO). We implement experiments to evaluate the performance of the F-Transform and MI similarity measures for 2-D/3-D rigid point feature registration. The experimental results showed that the proposed method produces totally accurate performance for rigid point feature registration for MRI brain images.
References
- N. Al-Azzawi, et al. , "Medical image fusion scheme using complex contourlet transform based on PCA," in Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2009, Hilton Minneapolis, Minnesota, USA, 2009, pp. 5813-5816.
- J. V. Hajnal, et al. , Medical image registration. Boca Raton: CRC Press, 2001.
- A. Goshtasby, 2-D and 3-D image registration for medical, remote sensing, and industrial applications. Hoboken, NJ: J. Wiley & Sons, 2005.
- S. Rusinkiewicz and M. Levoy, "Efficient variants of the ICP algorithm," in Proceedings Third International Conference on 3-D Digital Imaging and Modeling, Quebec City, 2001, pp. 145-152.
- E. Meijering, et al. , "Tracking in molecular bioimaging," IEEE Signal Processing Magazine, vol. 23, pp. 46-53, 2006.
- B. Zitova and J. Flusser, "Image registration methods: A survey," Image and Vision Computing, vol. 21, pp. 977-1000, 2003.
- J. Canny, "A computational approach to edge detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. , PAMI-8, pp. 679 –698, Nov. 1986.
- A. Rangarajan, et al. , "Rigid point feature registration using mutual information," Medical Image Analysis, vol. 3, pp. 425-440, 1999.
- I. Perfilieva, "Fuzzy transforms: Theory and applications," Fuzzy Sets and Systems, vol. 157, pp. 993-1023, 2006.
- I. Perfilieva, et al. , "Image fusion on the basis of fuzzy transforms," in The 8th International FLINS Conference on Computational Intelligence in Decision and Control, Madrid, Spain, 2008, pp. 471–476.
- M. Dankova, et al. , "Edge detection using F-transform," in Intelligent Systems Design and Applications (ISDA), 2011 11th International Conference on, 2011, pp. 672-677.
- F. Yang and H. -L. Zhang, "Multiresolution 3D image registration using hybrid ant colony algorithm and powell's method," Journal of Electronics and Information Technology, vol. 29, pp. 622-625, 2007.
- A. V. Tuzikov, et al. , "Evaluation of the symmetry plane in 3D MR brain images," Pattern Recognition Letters, vol. 24, pp. 2219-2233, 2003.
- B. Birge, "PSOt - a particle swarm optimization toolbox for use with Matlab," in Proceedings of the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03, Indianapolis (IN), USA, 2003, pp. 182-186.
- J. Kennedy and R. C. Eberhart, "Particle swarm optimization," in Proceedings of IEEE International Conference on Neural Networks, Piscataway, NJ, 1995, pp. 1942-1948.
- I. Perfilieva, "Fuzzy transforms: A challenge to conventional transforms," in Advances in Images and Electron Physics. vol. 147, ed San Diego: Elsevier Academic Press, 2007, pp. 137-196.
- I. Perfilieva and R. Valášek, "Fuzzy Transforms in Removing Noise Computational Intelligence, Theory and Applications. " vol. 33, B. Reusch, Ed. , ed: Springer Berlin / Heidelberg, 2005, pp. 221-230.
- J. P. W. Pluim, et al. , "Mutual-information-based registration of medical images: a survey," IEEE Transactions on Medical Imaging, vol. 22, pp. 986-1004, 2003.
- A. Gholipour, et al. , "Brain functional localization: A survey of image registration techniques," IEEE Transactions on Medical Imaging, vol. 26, pp. 427-451, 2007.
- F. Maes, et al. , "Multimodality image registration by maximization of mutual information," IEEE Transactions on Medical Imaging, vol. 16, pp. 187-198, 1997.
- N. Al-Azzawi and W. A. K. W. Abdullah, "MRI Monomodal Feature-Based Registration Based on the Efficiency of Multiresolution Representation and Mutual Information," American Journal of Biomedical Engineering, vol. 2, pp. 98-104, 2012.
- L. G. Brown, "A survey of image registration techniques," ACM Computing Surveys, vol. 24, pp. 325-376, 1992.
- A. E. R. Arce-Santana and A. Alba, "Image registration using Markov random coefficient and geometric transformation fields " Pattern Recognition vol. 42, pp. 1660-1671, 2009.
Index Terms
Keywords