Literature DB >> 27370900

Retinal image registration under the assumption of a spherical eye.

Carlos Hernandez-Matas1, Xenophon Zabulis2, Areti Triantafyllou3, Panagiota Anyfanti3, Antonis A Argyros1.   

Abstract

We propose a method for registering a pair of retinal images. The proposed approach employs point correspondences and assumes that the human eye has a spherical shape. The image registration problem is formulated as a 3D pose estimation problem, solved by estimating the rigid transformation that relates the views from which the two images were acquired. Given this estimate, each image can be warped upon the other so that pixels with the same coordinates image the same retinal point. Extensive experimental evaluation shows improved accuracy over state of the art methods, as well as robustness to noise and spurious keypoint matches. Experiments also indicate the method's applicability to the comparative analysis of images from different examinations that may exhibit changes and its applicability to diagnostic support.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Medical imaging; Particle Swarm Optimization; Pose estimation; Retinal image registration

Mesh:

Year:  2016        PMID: 27370900     DOI: 10.1016/j.compmedimag.2016.06.006

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  5 in total

1.  Deep-learning based multi-modal retinal image registration for the longitudinal analysis of patients with age-related macular degeneration.

Authors:  Tharindu De Silva; Emily Y Chew; Nathan Hotaling; Catherine A Cukras
Journal:  Biomed Opt Express       Date:  2020-12-23       Impact factor: 3.732

2.  Joint alignment of multispectral images via semidefinite programming.

Authors:  Yuanjie Zheng; Yu Wang; Wanzhen Jiao; Sujuan Hou; Yanju Ren; Maoling Qin; Dewen Hou; Chao Luo; Hong Wang; James Gee; Bojun Zhao
Journal:  Biomed Opt Express       Date:  2017-01-17       Impact factor: 3.732

3.  Laplacian feature detection and feature alignment for multimodal ophthalmic image registration using phase correlation and Hessian affine feature space.

Authors:  Shan Suthaharan; Ethan A Rossi; Valerie Snyder; Jay Chhablani; Raphael Lejoyeux; Jośe-Alain Sahel; Kunal Dansingani
Journal:  Signal Processing       Date:  2020-08-11       Impact factor: 4.662

4.  Grey-Wolf-Based Wang's Demons for Retinal Image Registration.

Authors:  Sayan Chakraborty; Ratika Pradhan; Amira S Ashour; Luminita Moraru; Nilanjan Dey
Journal:  Entropy (Basel)       Date:  2020-06-15       Impact factor: 2.524

5.  Quantitative Fundus Autofluorescence: Advanced Analysis Tools.

Authors:  Nikolai Kleefeldt; Katharina Bermond; Ioana-Sandra Tarau; Jost Hillenkamp; Andreas Berlin; Kenneth R Sloan; Thomas Ach
Journal:  Transl Vis Sci Technol       Date:  2020-07-01       Impact factor: 3.283

  5 in total

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