Landmark matching based retinal image alignment by enforcing sparsity in correspondence matrix.
Retinal image alignment is fundamental to many applications in diagnosis of eye diseases. In this paper, we address the problem of landmark matching based retinal image alignment. We propose a novel landmark matching formulation by enforcing sparsity in the correspondence matrix and offer its solutions based on linear programming. The proposed formulation not only enables a joint estimation of the landmark correspondences and a predefined transformation model but also combines the benefits of the softassign strategy (Chui and Rangarajan, 2003) and the combinatorial optimization of linear programming. We also introduced a set of reinforced self-similarities descriptors which can better characterize local photometric and geometric properties of the retinal image. Theoretical analysis and experimental results with both fundus color images and angiogram images show the superior performances of our algorithms to several state-of-the-art techniques.
Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA. Electronic address: Yuanjie.Zheng@uphs.upenn.edu.
Yuanjie
Y
Zheng
Department of Ophthalmology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
Ebenezer
E
Daniel
Department of Ophthalmology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
Allan A
AA
Hunter
Department of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
Rui
R
Xiao
University of Electronic Science and Technology, Chengdu, Sichuan, China.
Jianbin
J
Gao
University of Electronic Science and Technology, Chengdu, Sichuan, China.
Hongsheng
H
Li
Department of Ophthalmology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
Maureen G
MG
Maguire
Department of Psychology, School of Arts and Sciences at the University of Pennsylvania, Philadelphia, PA, USA.
David H
DH
Brainard
Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
James C
JC
Gee
D000465:Algorithms; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011382:Programming, Linear; D015203:Reproducibility of Results; D012160:Retina / Q000033:anatomy & histology*; D042262:Retinoscopy / Q000379:methods*; D012680:Sensitivity and Specificity; D013382:Subtraction Technique
Image alignment; Point matching; Retinal image; Sparsity; Transformation