Dynamic optical imaging of retinal hemodynamics is a rapidly evolving technique in vision and eye-disease research. Video-recording, which may be readily accessible and affordable, captures several distinct functional phenomena such as the spontaneous venous pulsations (SVP) of central vein or local arterial blood supply etc. These phenomena display specific dynamic patterns that have been detected using manual or semi-Automated methods. We propose a pioneering concept in retina video-imaging using blind source separation (BSS) serving as an automated localizer of distinct areas with temporally synchronized hemodynamics. The feasibility of BSS techniques (such as spatial principal component analysis and spatial independent component analysis) and K-means based post-processing method were successfully tested on the monocular and binocular video-ophthalmoscopic (VO) recordings of optic nerve head (ONH) in healthy subjects. BSSs automatically detected three spatially distinct reproducible areas, i.e. SVP, optic cup pulsations (OCP) that included areas of larger vessels in the nasal part of ONH, and 'other' pulsations (OP). The K-means post-processing reduced a spike noise from the patterns' dynamics while high linear dependence between the non-filtered and post-processed signals was preserved. Although the dynamics of all patterns were heart rate related, the morphology analysis demonstrated significant phase shifts between SVP and OCP, and between SVP and OP. In addition, we detected low frequency oscillations that may represent respiratory-induced effects in time-courses of the VO recordings.
Bibliographical noteFunding Information:
Manuscript received September 13, 2020; accepted November 16, 2020. Date of publication November 24, 2020; date of current version March 2, 2021. This work was supported in part by the Brno University of Technology under Grant FEKT-S-17-4487, in part by the Czech Health Research Council under Grant NV17-29452A, and in part by the Department of Pediatrics, University of Minnesota with “Progressive” grant. (Corresponding author: Radim Kolar.) Ivana Labounkova is with the Department of Biomedical Engineering, Brno University of Technology, 61200 Brno, Czech Republic, and also with the Department of Pediatrics, University of Minnesota, Minneapolis, MN 55414 USA (e-mail: email@example.com).
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- Blind source separation
- independent component analysis
- optic nerve head
- principal component analysis
- spontaneous venous pulsations