Title
RERBEE: Robust Efficient Registration via Bifurcations and Elongated Elements Applied to Retinal Fluorescein Angiogram Sequences
Abstract
We present RERBEE (robust efficient registration via bifurcations and elongated elements), a novel feature-based registration algorithm able to correct local deformations in high-resolution ultra-wide field-of-view (UWFV) fluorescein angiogram (FA) sequences of the retina. The algorithm is able to cope with peripheral blurring, severe occlusions, presence of retinal pathologies and the change of image content due to the perfusion of the fluorescein dye in time. We have used the computational power of a graphics processor to increase the performance of the most computationally expensive parts of the algorithm by a factor of over × 1300, enabling the algorithm to register a pair of 3900 × 3072 UWFV FA images in 5-10 min instead of the 5-7 h required using only the CPU. We demonstrate accurate results on real data with 267 image pairs from a total of 277 (96.4%) graded as correctly registered by a clinician and 10 (3.6%) graded as correctly registered with minor errors but usable for clinical purposes. Quantitative comparison with state-of-the-art intensity-based and feature-based registration methods using synthetic data is also reported. We also show some potential usage of a correctly aligned sequence for vein/artery discrimination and automatic lesion detection.
Year
DOI
Venue
2012
10.1109/TMI.2011.2167517
Medical Imaging, IEEE Transactions
Keywords
Field
DocType
bifurcation,biomedical optical imaging,dyes,eye,fluorescence,image registration,medical image processing,RERBEE,Robust Efficient Registration via Bifurcations and Elongated Elements,artery discrimination,automatic lesion detection,feature based registration algorithm,fluorescein dye perfusion,local deformation correction,occlusions,peripheral blurring,retinal fluorescein angiogram sequences,retinal pathology,time 5 h to 7 h,time 5 min to 10 min,vein discrimination,Deformable registration,fluorescein angiogram,graphics processing unit (GPU),retina
Graphics,Computer vision,Central processing unit,Computer science,Fluorescein angiography,Feature extraction,Image segmentation,Synthetic data,Artificial intelligence,Graphics processing unit,Image registration
Journal
Volume
Issue
ISSN
31
1
0278-0062
Citations 
PageRank 
References 
1
0.36
0
Authors
6
Name
Order
Citations
PageRank
Adria Perez-Rovira111.37
R. Cabido210310.09
Emanuele Trucco31236116.32
Stephen McKenna41475223.16
Jean Pierre Hubschman561.73
Perez-Rovira, A.610.36