Stereo matching and 3-d reconstruction for optic disk images

Authors:
Kai Zhang;Xu Xi;Zhang Li;Wang Guoping
Affiliations:
School of Electronics Engineering and Computer Science, Peking University, China;Department of Clinical Medicine, The First Military Medical University, China;Ophthalmology Center, The Fifth People’s Hospital of Foshan, China;School of Electronics Engineering and Computer Science, Peking University, China
Venue:
CVBIA'05 Proceedings of the First international conference on Computer Vision for Biomedical Image Applications
Year:
2005

Citing 6
Cited 0

Probabilistic reasoning in intelligent systems: networks of plausible inference

Probabilistic reasoning in intelligent systems: networks of plausible inference
Depth Discontinuities by Pixel-to-Pixel Stereo

International Journal of Computer Vision
Mean Shift: A Robust Approach Toward Feature Space Analysis

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms

International Journal of Computer Vision
Stereo Matching Using Belief Propagation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Advances in Computational Stereo

IEEE Transactions on Pattern Analysis and Machine Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

3-D visualization of optic disk surface is very useful in diagnosis and observation of some eye diseases. It helps physicians in understanding and interpreting the stereo disc photographs(SDPs) which is widely used in clinical situations. This paper proposed a segment-based stereo matching algorithm, which represents the fundus structure as a Bayesian network and applies belief propagation(BP) to solve the maximum a posterior(MAX) estimation. Only ground control pixels(GCPs) of the BP results are retrieved and the dense disparity map is obtained by cubic interpolation and Gaussian blurring to ensure smoothness. The resulted 3-D retinal surface shows our approach is promising.