Optical imaging of retinal hemodynamic function is an important part of ophthalmologic research. Development and inventing of imaging devices and data analysis methods are both just in progress. The current study innovatively implements two blind source separation (BSS) techniques (i.e. spatial Principal Component Analysis - sPCA; and spatial Independent Component Analysis - sICA) in application of an automatic detection and segmentation of a distinct Optic Disc (OD) areas with different hemodynamic properties from a simultaneous binocular video-ophthalmoscopic records. Both methods detected 3 different spatial patterns mostly symmetric over both eyes stable and reproducible over investigated participants, i.e. central Spontaneous Vessel Pulsations (SVPs), inner OD intensity pulsations and other OD pulsations. Dynamics of all mentioned patterns has a periodic character with similar main frequency (possibly corresponding to subject-specific heart rate) but shifted phase decreasing patterns' mutual high cross-correlations. The sICA estimates a higher rate of phase shifts than sPCA.
|Original language||English (US)|
|Title of host publication||2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||4|
|State||Published - Jul 2019|
|Event||41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 - Berlin, Germany|
Duration: Jul 23 2019 → Jul 27 2019
|Name||Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS|
|Conference||41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019|
|Period||7/23/19 → 7/27/19|
Bibliographical noteFunding Information:
Research supported by Brno University of Technology grant n. FEKTS- 17-4487, Czech Health Research Council grant n. NV17-29452A, and by Department of Pediatrics, University of Minnesota with Progressive grant.
PubMed: MeSH publication types
- Journal Article
- Research Support, Non-U.S. Gov't