DocumentCode :
1761306
Title :
Vessel-based registration of fundus and optical coherence tomography projection images of retina using a quadratic registration model
Author :
Golabbakhsh, Marzieh ; Rabbani, Hossein
Author_Institution :
Biomed. Eng. Dept., Isfahan Univ. of Med. Sci., Isfahan, Iran
Volume :
7
Issue :
8
fYear :
2013
fDate :
41579
Firstpage :
768
Lastpage :
776
Abstract :
The new techniques of three-dimensional (3D)-optical coherence tomography (OCT) imaging is very useful for detecting retinal pathologic changes in various diseases and determining retinal thickness `abnormalities´. Fundus colour images have been used for several years for detecting retinal abnormalities too. If the two image modalities were combined, the resulted image would be more informative. The first step to combine these two modalities is to register colour fundus images with an en face representation of OCT. In this study, curvelet transform is used to extract vessels for both modalities. Then the extracted vessels from two modalities are registered together in two stages. At first, images are registered using scaling and translation transformations. Then a quadratic transformation model is assumed between two pairs of images; because retina is imaged as a second-order surface. Twenty-two eyes (17 macular and 5 prepapillary), from random patients, were imaged in this study with Topcon 3D OCT1000 instrument. A new registration error is defined which averages the distance between all the corresponding points in two sets of vessels. Results show that registration error after stage one is 6.01 ± 1.82 pixels and after stage two is 1.02 ± 0.02 pixels.
Keywords :
curvelet transforms; diseases; eye; feature extraction; image colour analysis; image registration; image representation; image sensors; learning (artificial intelligence); least squares approximations; medical image processing; optical projectors; optical tomography; retinal recognition; search problems; Topcon 3D OCT-imaging; colour fundus image detection; colour fundus image registration; curvelet transform; disease; face representation; geographic atrophy; image modality; k-nearest neighbour search; least square method; macular hemorrhage; optical coherence tomography projection imaging; quadratic registration model; quadratic transformation model; retinal pathologic detection; retinal thickness abnormality determination; scaling transformation; second-order surface; three-dimensional-optical coherence tomography imaging; translation transformation; vessel-based fundus registration;
fLanguage :
English
Journal_Title :
Image Processing, IET
Publisher :
iet
ISSN :
1751-9659
Type :
jour
DOI :
10.1049/iet-ipr.2013.0116
Filename :
6668038
Link To Document :
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