Publication detail

Comprehensive automatic processing and analysis of adaptive optics flood illumination retinal images on healthy subjects

VALTEROVÁ, E. UNTERLAUFT, J. FRANCKE, M. TORALF, K. KOLÁŘ, R. RAUSCHER, F.

Original Title

Comprehensive automatic processing and analysis of adaptive optics flood illumination retinal images on healthy subjects

Type

journal article in Web of Science

Language

English

Original Abstract

This work presents a novel fully automated method for retinal analysis in images acquired with a flood illuminated adaptive optics retinal camera (AO-FIO). The proposed processing pipeline consists of several steps: First, we register single AO-FIO images in a montage image capturing a larger retinal area. The registration is performed by combination of phase correlation and the scale-invariant feature transform method. A set of 200 AO-FIO images from 10 healthy subjects (10 images from left eye and 10 images from right eye) is processed into 20 montage images and mutually aligned according to the automatically detected fovea center. As a second step, the photoreceptors in the montage images are detected using a method based on regional maxima localization, where the detector parameters were determined with Bayesian optimization according to manually labeled photoreceptors by three evaluators. The detection assessment, based on Dice coefficient, ranges from 0.72 to 0.8. In the next step, the corresponding density maps are generated for each of the montage images. As a final step, representative averaged photoreceptor density maps are created for the left and right eye and thus enabling comprehensive analysis across the montage images and a straightforward comparison with available histological data and other published studies. Our proposed method and software thus enable us to generate AO-based photoreceptor density maps for all measured locations fully automatically, and thus it is suitable for large studies, as those are in pressing need for automated approaches. In addition, the application MATADOR (MATlab ADaptive Optics Retinal Image Analysis) that implements the described pipeline and the dataset with photoreceptor labels are made publicly available.

Keywords

retinal imaging; adaptive optics; cone detection; image procesing

Authors

VALTEROVÁ, E.; UNTERLAUFT, J.; FRANCKE, M.; TORALF, K.; KOLÁŘ, R.; RAUSCHER, F.

Released

30. 1. 2023

Publisher

Optica Publishing Group

ISBN

2156-7085

Periodical

Biomedical Optics Express

Year of study

14

Number

2

State

United States of America

Pages from

945

Pages to

970

Pages count

26

URL

https://opg.optica.org/boe/fulltext.cfm?uri=boe-14-2-945&id=525618

Full text in the Digital Library

http://hdl.handle.net/11012/209510

BibTex

@article{BUT183111,
  author="Eva {Orságová} and Jan D. {Unterlauft} and Mike {Francke} and Kirsten {Toralf} and Radim {Kolář} and Franziska G. {Rauscher}",
  title="Comprehensive automatic processing and analysis of adaptive optics flood illumination retinal images on healthy subjects",
  journal="Biomedical Optics Express",
  year="2023",
  volume="14",
  number="2",
  pages="945--970",
  doi="10.1364/BOE.471881",
  issn="2156-7085",
  url="https://opg.optica.org/boe/fulltext.cfm?uri=boe-14-2-945&id=525618"
}