Fully Automated Quantification of Synaptic Localization in Multi-channel Drosophila Photoreceptor Microscopy Data

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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
The workload posed by image analysis remains a major bottleneck for advances across the life sciences. To address this challenge, we have developed a fully automated workflow for processing complex 3D multi-channel microscopy images. Specifically, our workflow addresses the analysis of photoreceptor synapses in confocal images of the Drosophila melanogaster optic lobe. The workflow consists of multiple stages, combining traditional and machine learning-based approaches for image analysis and visual computing. It performs segmentation of brain regions, photoreceptor instance identification, and precise localization of synapses. The key novelty of the workflow is an automatic alignment of synapses into a cylindrical reference coordinate system, enabling comparative synaptic analysis across photoreceptors. To demonstrate the workflow's applicability, preliminary biological results and their interpretation based on 50 images are presented. While the workflow is still being improved further, here, we showcase its capacity for efficient and objective data processing for high-throughput neurobiological analyses.
Description

CCS Concepts: Applied computing → Bioinformatics; Human-centered computing → Scientific visualization

        
@inproceedings{
10.2312:vcbm.20251254
, booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine
}, editor = {
Garrison, Laura
and
Krueger, Robert
}, title = {{
Fully Automated Quantification of Synaptic Localization in Multi-channel Drosophila Photoreceptor Microscopy Data
}}, author = {
Brence, Blaz
and
Fuchs, Joachim
and
Hiesinger, Peter Robin
and
Baum, Daniel
}, year = {
2025
}, publisher = {
The Eurographics Association
}, ISSN = {
2070-5786
}, ISBN = {
978-3-03868-276-9
}, DOI = {
10.2312/vcbm.20251254
} }
Citation