June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
Periodic axial motion estimation and correction using low-cost optical coherence tomography (OCT)
Author Affiliations & Notes
  • Anirudh Ashok
    Carl Zeiss Meditec, Inc., Dublin, California, United States
  • Homayoun Bagherinia
    Carl Zeiss Meditec, Inc., Dublin, California, United States
  • Footnotes
    Commercial Relationships   Anirudh Ashok Carl Zeiss Meditec, Inc., Dublin, CA, United States, Code E (Employment); Homayoun Bagherinia Carl Zeiss Meditec, Inc., Dublin, CA, United States, Code E (Employment)
  • Footnotes
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Investigative Ophthalmology & Visual Science June 2022, Vol.63, 3311 – F0120. doi:
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    • Get Citation

      Anirudh Ashok, Homayoun Bagherinia; Periodic axial motion estimation and correction using low-cost optical coherence tomography (OCT). Invest. Ophthalmol. Vis. Sci. 2022;63(7):3311 – F0120.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Motion artifacts in OCT imaging have been an important topic in OCT data analysis. Periodic motion artifacts during OCT image acquisition of a patient can be caused by various sources such as muscular, peristaltic, cardiovascular, respiratory, as well as mechanical vibration in the instrument. Here we present a new periodic motion correction method for OCT data. We demonstrate the performance of the method by evaluating RPE (retinal pigment epithelium) elevation with and without motion correction.

Methods : Our method uses ILM (internal limiting membrane) and RPE segmentation in low-cost OCT volume scans. The Fourier transformation of ILM layer is used to estimate the periodic motion. The frequency bands associated with periodic pattern were removed prior to the inverse Fourier transformation. The estimated motion is then used to remove periodic motion artifact from the RPE layer. A polynomial surface is fitted to the RPE layer (RPE-fit) to mimic Bruch’s membrane. The RPE elevation map is created by measuring the difference between the RPE-fit and RPE surfaces. We evaluated this method using scans from 17 subjects, either left or right eye, with retinal pathology. Each eye was scanned twice using a prototype low-cost OCT device that had a macula scan with 128x512 A-scans over 7x5.8 mm. The RPE elevation map from the 2nd scan was registered to that of the 1st scan. The RPE elevation volumes (in cubic micrometers) were averaged over central 3-mm and 5-mm zones. Regression and Bland-Altman plots were derived to evaluate the agreement of RPE elevation map.

Results : Figure 1 shows the algorithm pipeline and examples of RPE elevation maps with and without periodic motion correction. Figure 2 illustrates the Bland-Altman plots comparing the RPE elevation volume (in cubic micrometers) of the two scans from the same eye in the central 3-mm and 5-mm zones. Our results show that there is a good correlation agreement between the two methods. The method with motion correction shows smaller mean difference and tighter 95% confidence interval, which indicate a more repeatable method.

Conclusions : We presented a method to compensate for periodic motion in low-cost OCT data prior to the RPE elevation map creation. We demonstrated that the motion compensation is essential for visualization of the RPE elevation map as well as better agreement between repeat scans.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.

 

 

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