Blind Source Separation of Retinal Pulsatile Patterns in Optic Nerve Head Video-Recordings

Heart rate and age modulate retinal pulsatile patterns

“…The principles of image acquisition were previously described 16 . In short, both available video-ophthalmoscope types (monocular and binocular) acquire images of the reflected light intensity modulated by heart rate induced attenuation changes 16 , 26 . Because such changes are caused by spatial-temporal retinal blood volume changes, the lowest pixel image intensity corresponds to the highest blood volume (and the highest attenuation) and vice versa.…”

“…Left eye monocular RVRs were acquired with the monocular video-ophthalmoscope consisting of the optical lens system (40D ophthalmic lens, two achromatic lenses), one monochrome CCD camera (UI-2210 SE-M-GL, USB interface, iDS, Germany ), red LED forming the fixation target, and a low power narrow-band LED (wavelength λ = 575 nm) illuminating retina with 30 μW/cm 2 . Acquired 10 s video sequences were saved in non-compressed AVI format with 25 fps (frames-per-second) and matrix size 640 × 480 pixels covering 20° × 15° field of view (i.e., 1 pixel ≈ 9.3 × 9.3 μm 2 16 , 26 , 51 ).…”

“…However, the reproducibility of the parameters remains a challenge due to the uniqueness of each individual’s retinal vessel tree 24 and the bias introduced by a subjective inter-rater and inter-participant selection of analyzed morphological segments 25 . To increase the reproducibility of local retinal hemodynamics, we have recently implemented a blind source separation that automatically divided the optic nerve head (ONH) into 2-3 functionally distinct areas that emerged as specific retinal pulsatile patterns (RPPs) 26 . The reproducible RPPs were spontaneous venous pulsation (SVP) and optic cup pulsation (OCP) with mutually phase-shifted hemodynamics.…”

“…The reproducible RPPs were spontaneous venous pulsation (SVP) and optic cup pulsation (OCP) with mutually phase-shifted hemodynamics. OCP was postulated to represent arterial blood filling preceding the SVP outflow 26 .…”

Blind Source Separation Based on Quantum Slime Mould Algorithm in Impulse Noise

“…BSS is a signal processing method that extracts or restores each component of the source signal only through the received observation signals without any prior knowledge of the source signals and the transmission channels. BSS has gradually become a research hotspot and has been successfully applied in various fields, such as image and voice signal processing, biomedical signal analysis and processing, or antenna array signal processing [1][2][3]. However, the current BSS methods still have many shortcomings.…”