bioRxiv : the preprint server for biology · 2026
3D-MAESTRO: A scalable, modular, portable pipeline for automated processing of large-scale volumetric brain microscopy data.
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Laiton Camilo, Lusk Nicholas, Browning Yoni, Summers Mathew T, Taormina Michael, Wang Di, Siegle Joshua H, Myers Holly, Tan Bowen, Kosillo Polina, Peterson Erica, Toglia Daphne, Lakunina Anna, Burckhardt Sasha, Young Jon, Kapoor Mekhla, Wang Tim, Rohde John, Lynch Galen, Yao Shenqin, Narayan Sujatha, Hooper Marcus, Way Sharon W, Waters Jack, Tasic Bosiljka, Chandrashekar Jayaram, Glaser Adam, Feng David, Seshamani Sharmishtaa, Svoboda Karel
Аннотация
Light microscopy is routinely used to explore the cellular and molecular structure of tissues, but the scale and complexity of data remains a bottleneck for discovery. We introduce 3D-MAESTRO (3D-Microscopy Automation and Execution with Scalable Tools, Rendering, and Orchestration): an automated image processing workflow for large-scale microscopy data, built for scalable execution across cloud and local computing environments. 3D-MAESTRO orchestrates denoising, stitching of image tiles, atlas registration, and segmentation. Its modular architecture permits the integration and benchmarking of new packages, ensuring that performance evolves as more efficient or accurate algorithms emerge. We introduce a new 3D image template for automated registration of mouse brains cleared with aqueous reagents and an efficient method for detection of fluorescent cells. We apply 3D-MAESTRO to lightsheet images of whole mouse brains in the context of diverse anatomical and functional experiments, illustrating high-throughput and reproducible mapping of microscopic structures across the brain.