Characterization of retinal arteries by adaptive optics ophthalmoscopy image analysis.
IEEE Trans Biomed Eng
; PP2024 Jun 03.
Article
in En
| MEDLINE
| ID: mdl-38829761
ABSTRACT
OBJECTIVE:
This paper aims at quantifying biomarkers from the segmentation of retinal arteries in adaptive optics ophthalmoscopy images (AOO).METHODS:
The segmentation is based on the combination of deep learning and knowledge-driven deformable models to achieve a precise segmentation of the vessel walls, with a specific attention to bifurcations. Biomarkers (junction coefficient, branching coefficient, wall to lumen ratio (wlr) are derived from the resulting segmentation.RESULTS:
reliable and accurate segmentations (mse = 1.75 ± 1.24 pixel) and measurements are obtained, with high reproducibility with respect to images acquisition and users, and without bias.SIGNIFICANCE:
In a preliminary clinical study of patients with a genetic small vessel disease, some of them with vascular risk factors, an increased wlr was found in comparison to a control population.CONCLUSION:
The wlr estimated in AOO images with our method (AOV, Adaptive Optics Vessel analysis) seems to be a very robust biomarker as long as the wall is well contrasted.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
IEEE Trans Biomed Eng
Year:
2024
Document type:
Article