Highly adaptable deep-learning platform for automated detection and analysis of vesicle exocytosis.
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| Title: | Highly adaptable deep-learning platform for automated detection and analysis of vesicle exocytosis. |
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| Authors: | Chouaib, Abed Alrahman, Chang, Hsin-Fang, Khamis, Omnia M., Alawar, Nadia, Echeverry, Santiago, Demeersseman, Lucie, Elizarova, Sofia, Daniel, James A., Tian, Qinghai, Lipp, Peter, Fornasiero, Eugenio F., Valitutti, Salvatore, Barg, Sebastian, Pape, Constantin, Shaib, Ali H., Becherer, Ute |
| Source: | Nature Communications; 7/12/2025, Vol. 16 Issue 1, p1-18, 18p |
| Subject Terms: | DEEP learning, EXOCYTOSIS, NEURAL transmission, HUMAN activity recognition, SOFTWARE development tools, ALGORITHMS, FLUORIMETRY, CELL imaging |
| Abstract: | Activity recognition in live-cell imaging is labor-intensive and requires significant human effort. Existing automated analysis tools are largely limited in versatility. We present the Intelligent Vesicle Exocytosis Analysis (IVEA) platform, an ImageJ plugin for automated, reliable analysis of fluorescence-labeled vesicle fusion events and other burst-like activity. IVEA includes three specialized modules for detecting: (1) synaptic transmission in neurons, (2) single-vesicle exocytosis in any cell type, and (3) nano-sensor-detected exocytosis. Each module uses distinct techniques, including deep learning, allowing the detection of rare events often missed by humans at a speed estimated to be approximately 60 times faster than manual analysis. IVEA's versatility can be expanded by refining or training new models via an integrated interface. With its impressive speed and remarkable accuracy, IVEA represents a seminal advancement in exocytosis image analysis and other burst-like fluorescence fluctuations applicable to a wide range of microscope types and fluorescent dyes. Activity recognition in live-cell imaging is laborious. Here, authors present, IVEA, a fully automated AI ImageJ plugin, that efficiently detects and classifies exocytosis events, from synaptic transmission to single-vesicle fusion, across cell types and imaging setups. [ABSTRACT FROM AUTHOR] |
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| Database: | Complementary Index |
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