Abstract
Purpose :
Optical coherence tomography (OCT) can be used to image and monitor cells in the anterior chamber due to conditions such as iritis. However, detailed analysis of individual moving cells such as spectroscopic analysis may require tracking over multiple OCT volumes. Therefore, we propose efficient cell tracking using adaptive scanning OCT (Fig. 1) based on cornea-removed maximum intensity projections (MIPs).
Methods :
First, we used a real-time graph-search algorithm to segment and remove the cornea from OCT volumes. Next, the adaptive scanning algorithm utilized cornea-removed MIPs to identify targets of interest (cells) and their direction of motion to plan and adapt subsequent scan patterns. For analysis, we determined the A-scan location of the centroid for cells tracked across >15 volumes and then averaged the A-scans to improve the signal-to-noise ratio (SNR). The program updated the cell list if a new cell appeared or existing cells moved to a new position in the new volume. To test this approach, we used 10 µm radius polystyrene microbeads as cell phantoms. A custom SS-OCT system with a spot size radius of 32.2 µm was used to image an artificial anterior chamber with a phantom silicon rubber cornea after injection of a 0.17% microbead solution. 5 artificial anterior chambers were imaged, each for a minimum of 73 sequential OCT volumes.
Results :
Example results are shown in Fig. 2. Compared with a simple raster scan pattern, the adaptive scan demonstrated up to 3.6× improvement (2540 ms/vol vs. 698 ms/vol) in the volume refresh rate. For each anterior chamber, a mean of 64.6 ± 17.5 microbeads were successfully tracked for at least 15 volumes.
Conclusions :
With a higher OCT volume refresh rate by utilizing adaptive scanning, our cell tracking algorithm can efficiently track cells’ movement for future cell size classification and cell density estimation.
This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.