Fully Automated Quantification of Synaptic Locations in Multi-channel Drosophila Photoreceptor Microscopy Data
| dc.contributor.author | Brence, Blaz | en_US |
| dc.contributor.author | Fuchs, Joachim | en_US |
| dc.contributor.author | Hiesinger, Peter Robin | en_US |
| dc.contributor.author | Baum, Daniel | en_US |
| dc.contributor.editor | Garrison, Laura | en_US |
| dc.contributor.editor | Krueger, Robert | en_US |
| dc.date.accessioned | 2025-09-24T09:12:08Z | |
| dc.date.available | 2025-09-24T09:12:08Z | |
| dc.date.issued | 2025 | |
| dc.description.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. | en_US |
| dc.description.sectionheaders | Session 3 | |
| dc.description.seriesinformation | Eurographics Workshop on Visual Computing for Biology and Medicine | |
| dc.identifier.doi | 10.2312/vcbm.20251254 | |
| dc.identifier.isbn | 978-3-03868-276-9 | |
| dc.identifier.issn | 2070-5786 | |
| dc.identifier.pages | 5 pages | |
| dc.identifier.uri | https://doi.org/10.2312/vcbm.20251254 | |
| dc.identifier.uri | https://diglib.eg.org/handle/10.2312/vcbm20251254 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.rights | Attribution 4.0 International License | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | CCS Concepts: Applied computing → Bioinformatics; Human-centered computing → Scientific visualization | |
| dc.subject | Applied computing → Bioinformatics | |
| dc.subject | Human centered computing → Scientific visualization | |
| dc.title | Fully Automated Quantification of Synaptic Locations in Multi-channel Drosophila Photoreceptor Microscopy Data | en_US |