S-cone identification using AO-OCT cone structural measurements and support vector machine classifier

Qiuzhi Ji; Marcel T. Bernucci; Yan Liu; James A. Crowell; Davin J. Miller; Donald T. Miller

doi:10.1117/12.2650609

14 March 2023 S-cone identification using AO-OCT cone structural measurements and support vector machine classifier

Qiuzhi Ji, Marcel T. Bernucci, Yan Liu, James A. Crowell, Davin J. Miller, Donald T. Miller

Proceedings Volume 12360, Ophthalmic Technologies XXXIII; 1236005 (2023) https://doi.org/10.1117/12.2650609
Event: SPIE BiOS, 2023, San Francisco, California, United States

Abstract

The high resolution of adaptive optics optical coherence tomography (AO-OCT) allows 3-dimensional imaging of individual cone photoreceptors in vivo. Histology has revealed that short-wavelength-sensitive (S) cones have distinct structural features compared with medium-wavelength-sensitive (M) and long-wavelength-sensitive (L) cones. Quantifying these structural features in images of living human retinas may provide a simpler and quicker method for identifying S cones than by imaging cone function (e.g., optoretinography). Here, we present a quantitative method for using AO-OCT measurements of cone structure in a support vector machine (SVM) classifier to identify individual S cones. For every cone cell, we measured six key structural parameters: inner segment length (ISL), outer segment length (OSL), inner segment / outer segment conjunction (IS/OS) diameter, cone outer-segment tip (COST) diameter, IS/OS reflectance, and COST reflectance. ISL and OSL were determined from depth differences between reflections of the external limiting membrane (ELM) and IS/OS, and IS/OS and COST, respectively. Each reflection’s depth was measured with sub-pixel accuracy using Gaussian interpolation; its diameter was measured using the gradient information from the en face projection at that depth. Among 6,398 analyzed cones in six subjects, we found S cones had significantly longer ISLs, shorter OSLs, and wider IS/OS diameters than did cones of other types. We used these structural differences in our SVM model to classify cone spectral types and compared results with cone optoretinography. In five of the six subjects, S cones were identified with F1 scores ranging from 0.78 to 0.93.

Conference Presentation

Citation Download Citation

Qiuzhi Ji, Marcel T. Bernucci, Yan Liu, James A. Crowell, Davin J. Miller, and Donald T. Miller "S-cone identification using AO-OCT cone structural measurements and support vector machine classifier", Proc. SPIE 12360, Ophthalmic Technologies XXXIII, 1236005 (14 March 2023); https://doi.org/10.1117/12.2650609

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