This paper presents a disease-oriented evaluation of two recent retinal image registration algorithms, one for aligning pairs of retinal images and one for simultaneously aligning all images in a set. Medical conditions studied include diabetic retinopathy, vein occlusion, and both dry and wet age-related macular degeneration. The multi-image alignment worked virtually flawlessly, missing only 2 of 855 images. Pairwise registration, the Dual-Bootstrap ICP algorithm, worked nearly as well, successfully aligning 99.5% of the image pairs having a sufficient set of common features and 78.5% overall. Images of retinas having an edema and pairs of images taken before and after laser treatment proved the most difficult to register. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Tsai, C. L., Majerovics, A., Stewart, C. V., & Roysam, B. (2003). Disease-oriented evaluation of Dual-Bootstrap retinal image registration. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. https://doi.org/10.1007/978-3-540-39899-8_92
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