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S. Lee, J. M. Reinhardt, and M. Abramoff. Validation of Retinal Image Registration Algorithms by a Projective Imaging Distortion Model. In Proc IEEE Eng Med Biol Soc, vol. 1, pp. 6471-6474, 2007.

Abstract: Fundus camera imaging of the retina is widely used to document ophthalmologic disorders including diabetic retinopathy, glaucoma, and age-related macular degeneration. The retinal images typically have a limited field of view due mainly to the curvedness of human retina, so multiple images are to be joined together using image registration technique to form a montage with a larger field of view. A variety of methods for retinal image registration have been proposed, but evaluating such methods objectively is difficult due to the lack of a reference standard for the true alignment of the individual images that make up the montage. A method of generating simulated retinal image set by modeling geometric distortions due to the eye geometry and the image acquisition process is described in this paper. We also present the validation tool for any retinal image registration method by tracing back the distortion path and accessing the geometric misalignment from the coordinate system of reference standard. The quantitative comparison for different registration methods is given in the experiment, so the registration performance is evaluated in an objective manner.

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Keywords: registration retina

Other publications by: S. Lee, J. M. Reinhardt, M. Abramoff

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B. Li, G. E. Christensen, G. McLennan, E. A. Hoffman, and J. M. Reinhardt. Establishing a normative atlas of the human lung: Inter-subject warping and registration of volumetric CT. Acad. Radiol., vol. 10, no. 3, pp. 255-265, 2003. (details)
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Related conference papers:

S. Lee, M. Abramoff, and J. M. Reinhardt. Feature-based pairwise retinal image registration by radial distortion correction. In J. P. Pluim and J. M. Reinhardt, eds., Proc. SPIE Conf. Medical Imaging, vol. 6512, San Diego, CA, 2007. (details)
S. Lee, M. Abramoff, and J. M. Reinhardt. Retinal image mosaicing using the radial distortion correction model. In J. M. Reinhardt and J. P. Pluim, eds., Proc. SPIE Conf. Medical Imaging, vol. 6914, San Diego, CA, 2008. (details)
L. Zhang and J. M. Reinhardt. 3D pulmonary CT image registration with a standard lung atlas. In C.-T. Chen and A. V. Clough, eds., Proc. SPIE Conf. Medical Imaging, vol. 3978, pp. 67-77, San Diego, CA, 2000. (details)
F. Li, C.-W. Chen, E. A. Hoffman, and J. M. Reinhardt. Evaluation and application of 3D lung warping and registration model using HRCT images. In C.-T. Chen and A. V. Clough, eds., Proc. SPIE Conf. Medical Imaging, vol. 4321, pp. 234-243, San Diego, CA, 2001. (details)
B. Li, G. E. Christensen, J. Dill, E. A. Hoffman, and J. M. Reinhardt. 3-D inter-subject warping and registration of pulmonary CT images for a human lung model. In A. V. Clough and C.-T. Chen, eds., Proc. SPIE Conf. Medical Imaging, vol. 4683, pp. 324-335, San Diego, CA, 2002. (details)

Related theses:

S. Lee. A study of ophthalmologic imaging distortion for retinal image registration and validation. PhD thesis, The University of Iowa, Iowa City, IA, 2008. (details)
K. Ding. Registration-based regional lung mechanical analysis. MS thesis, The University of Iowa, Iowa City, IA, 2008. (details)
B. Li. The construction of a normative human lung atlas by inter-subject registration and warping of CT images. PhD thesis, The University of Iowa, Iowa City, IA, 2004. (details)
Y. Pan. Estimation of regional lung expansion via 3D image registration. MS thesis, The University of Iowa, Iowa City, IA, 2005. (details)
S. V. Bodas. Improved association graph matching of intra-patient airway trees. MS thesis, The University of Iowa, Iowa City, IA, 2008. (details)