Geometrically reconstructing confocal microscopy images for modelling the retinal microvasculature as a 3D cylindrical network

Evan P. Troendle*, Peter Barabas, Tim M. Curtis

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Microvascular networks can be modelled as a network of connected cylinders. Presently, however, there are limited approaches with which to recover these networks from biomedical images. We have therefore developed and implemented computer algorithms to geometrically reconstruct three-dimensional (3D) retinal microvascular networks from micrometre-scale imagery, resulting in a concise representation of two endpoints and radius for each cylinder detected within a delimited text file. This format is suitable for a variety of purposes, including efficient simulations of molecular delivery. Here, we detail a semi-automated pipeline consisting of the detection of retinal microvascular volumes within 3D imaging datasets, the enhancement and analysis of these volumes for reconstruction, and the geometric construction algorithm itself, which converts voxel data into representative 3D cylindrical objects.

Original languageEnglish
Title of host publicationProceedings of the 24th Irish Machine Vision and Image Processing Conference
PublisherIrish Pattern Recognition & Classification Society
Pages169-176
ISBN (Electronic)9780993420771
DOIs
Publication statusPublished - 31 Aug 2022
Event24th Irish Machine Vision and Image Processing Conference - Queen's University, Belfast, Belfast, United Kingdom
Duration: 31 Aug 202202 Sept 2022
Conference number: 24
https://imvipconference.github.io/
https://imvipconference.github.io/IMVIP2022_Proceedings.pdf

Conference

Conference24th Irish Machine Vision and Image Processing Conference
Abbreviated titleIMVIP
Country/TerritoryUnited Kingdom
CityBelfast
Period31/08/202202/09/2022
Internet address

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