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Effect of image registration on longitudinal analysis of retinal nerve fiber layer thickness of non-human primates using Optical Coherence Tomography (OCT)

Overview of attention for article published in Eye and Vision, February 2015
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Title
Effect of image registration on longitudinal analysis of retinal nerve fiber layer thickness of non-human primates using Optical Coherence Tomography (OCT)
Published in
Eye and Vision, February 2015
DOI 10.1186/s40662-015-0013-7
Pubmed ID
Authors

Shuang Liu, Anjali Datta, Derek Ho, Jordan Dwelle, Daifeng Wang, Thomas E Milner, Henry Grady Rylander, Mia K Markey

Abstract

In this paper we determined the benefits of image registration on estimating longitudinal retinal nerve fiber layer thickness (RNFLT) changes. RNFLT maps around the optic nerve head (ONH) of healthy primate eyes were measured using Optical Coherence Tomography (OCT) weekly for 30 weeks. One automatic algorithm based on mutual information (MI) and the other semi-automatic algorithm based on log-polar transform cross-correlation using manually segmented blood vessels (LPCC_MSBV), were used to register retinal maps longitudinally. We compared the precision and recall between manually segmented image pairs for the two algorithms using a linear mixed effects model. We found that the precision calculated between manually segmented image pairs following registration by LPCC_MSBV algorithm is significantly better than the one following registration by MI algorithm (p < <0.0001). Trend of the all-rings and temporal, superior, nasal and inferior (TSNI) quadrants average of RNFLT over time in healthy primate eyes are not affected by registration. RNFLT of clock hours 1, 2, and 10 showed significant change over 30 weeks (p = 0.0058, 0.0054, and 0.0298 for clock hours 1, 2 and 10 respectively) without registration, but stayed constant over time with registration. The LPCC_MSBV provides better registration of RNFLT maps recorded on different dates than the automatic MI algorithm. Registration of RNFLT maps can improve clinical analysis of glaucoma progression.

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Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 33%
Student > Master 2 17%
Student > Doctoral Student 2 17%
Other 1 8%
Unknown 3 25%
Readers by discipline Count As %
Engineering 3 25%
Medicine and Dentistry 2 17%
Mathematics 1 8%
Computer Science 1 8%
Business, Management and Accounting 1 8%
Other 2 17%
Unknown 2 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 November 2015.
All research outputs
#20,297,343
of 22,834,308 outputs
Outputs from Eye and Vision
#119
of 239 outputs
Outputs of similar age
#301,432
of 357,960 outputs
Outputs of similar age from Eye and Vision
#2
of 2 outputs
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