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

Background:In this paper we determined the benefits of image registration on estimating longitudinal retinal nerve fiber layer thickness(RNFLT)changes.Methods: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.Results: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.Conclusions: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.