Abstract:
Retinal images are routinely used in ophthalmology to study the optical nerve head and the retina. To assess objectively the evolution of an illness, images taken at diff...Show MoreMetadata
Abstract:
Retinal images are routinely used in ophthalmology to study the optical nerve head and the retina. To assess objectively the evolution of an illness, images taken at different times must be registered. Most methods so far have been designed specifically for a single image modality, like temporal series or stereo pairs of angiographies, fluorescein angiographies or scanning laser ophthalmoscope (SLO) images, which makes them prone to fail when conditions vary. In contrast, the method we propose has shown to be accurate and reliable on all the former modalities. It has been adapted from the 3D registration of CT and MR image to 2D. Relevant features (also known as landmarks) are extracted by means of a robust creaseness operator, and resulting images are iteratively transformed until a maximum in their correlation is achieved. Our method has succeeded in more than 100 pairs tried so far, in all cases including also the scaling as a parameter to be optimized.
Date of Conference: 03-07 September 2000
Date Added to IEEE Xplore: 06 August 2002
Print ISBN:0-7695-0750-6
Print ISSN: 1051-4651
References is not available for this document.
Select All
1.
J. Domingo, G. Ayala, A. Simó, E. de Ves, L. Martínez-Costa and P. Marco, Irregular motion recovery in fluorescein angiograms. Patter recognition letters, vol. 18, pp. 805-821, 1997.
2.
D. Lloret, A. López, J. Serrat and J. Villanueva, "Creaseness-based CT and MR registration: comparison with the mutual information method", Journal of Electronic Imaging, vol. 8, no. 3, pp. 255-262, July 1999.
3.
A. López, D. Lloret, J. Serrat and J. Villanueva, "Multilocal creasness based on the level set extrinsic curvature", Computer Vision and Image Understanding, no. 77, 2000.
4.
F. Maes, A. Collignon, D. Vandermeulen, G. Marchal and P. Suetens, "Multimodality image registration by maximization of mutual information", IEEE Trans. on Medical Imaging, vol. 16, no. 2, pp. 187-198, April 1997.
5.
J. Maintz and M. Viergever, "A survey of medical image registration", Medical Image Analysis, vol. 2, no. 1, pp. 1-36, 1998.
6.
L. Martinez-Costa, P. Marco, G. Ayala, E. de Ves, J. Domingo and A. Simó, "Macular edema computer-aided evaluation in ocular vein occlusions", Computers and biomedical research, vol. 31, pp. 374-384, 1998.
7.
M. E. Martínez-Pérez, A. D. Hughes, A. V. Stanton and S. A. Thom, "Retinal blood vessel segmentation by means of scale-space analysis and region growing", Medical image computing and computer-assisted intervention-MICCAI'99, vol. 1679, pp. 90-97, 1999.
8.
N. Ritter, R. Owens and J. Cooper, "Registration of stereo and temporal images of the retina", IEEE Transactions on Medical Imaging, vol. 18, no. 5, pp. 404-418, May 1999.
9.
Y. A. Tolias and S. M. Panas, "A fuzzy vessel tracking algorithm for retinal images based on funzzy clustering", IEEE Transactions on Medical Imaging, vol. 17, no. 2, pp. 263-273, April 1998.
10.
W. Wells, P. Viola, H. Atsumi, S. Nakajima and R. Kikinis, "Multi-modal volume registration by maximization of mutual information", Medical Image Analysis, vol. 1, no. 1, pp. 35-51, 1996.
11.
F. Zana and J. Klein, "A multimodal registration algorithm of eye fundus images using vessels detection and hough transform", IEEE transactions on Medical Imaging, vol. 18, no. 5, pp. 419-428, May 1999.
