Multimodal retinal image registration for optic disk segmentation.
OBJECTIVE
The analysis of the optic disk morphology with the means of the scanning laser tomography is an important step for glaucoma diagnosis. A method we developed for optic disk segmentation in images of the scanning laser tomograph is limited by noise, non-uniform illumination and presence of blood vessels. Inspired by recent medical research, we wanted to develop a tool for improving optic disk segmentation by registration of images of the scanning laser tomograph and color fundus photographs and by applying a method we developed for optic disk segmentation in color fundus photographs.


METHODS
The segmentation of the optic disk for glaucoma diagnosis in images of the scanning laser tomograph is based on morphological operations, detection of anatomical structures and active contours and has been described in a previous paper. The segmentation of the optic disk in the fundus photographs is based on nonlinear filtering, Canny edge detector and a modified Hough transform. The registration is based on mutual information using simulated annealing for finding maxima.


RESULTS
The registration was successful 86.8% of the time when tested on 174 images. Results of the registration have shown a very low displacement error of a maximum of about 5 pixels. The correctness of the registration was manually evaluated by measuring distances between the real vessel borders and those from the registered image.


CONCLUSIONS
We have developed a method for the registration of images of the scanning laser tomograph and fundus photographs. Our first experiments showed that the optic disk segmentation could be improved by fused information from both image modalities.
Chair for Pattern Recognition, Friedrich-Alexander-University, Erlangen, Germany. chrastek@informatik.uni-erlangen.de
R
R
Chrástek
M
M
Skokan
L
L
Kubecka
M
M
Wolf
K
K
Donath
J
J
Jan
G
G
Michelson
H
H
Niemann
D005654:Fundus Oculi; D005901:Glaucoma / Q000175:diagnosis*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007834:Lasers; D008491:Medical Informatics Applications; D009898:Optic Disk / Q000473:pathology*; D009901:Optic Nerve Diseases / Q000175:diagnosis*; D010781:Photography / Q000379:methods; D012160:Retina / Q000473:pathology; D014054:Tomography / Q000379:methods*