3D-MAESTRO: A scalable, modular, portable pipeline for automated processing of large-scale volumetric brain microscopy data
- 1Allen Institute
Abstract
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.
Related
- Cerebrovascular Structure-Flow Gradients Revealed by Volumetric Ultrasound Localization Microscopy
- NIR-II squeezed light-field microscopy enables high-speed volumetric imaging of deep-tissue dynamics in vivo
- Automated Volumetric Segmentation of Microaneurysms on OCT Using Artificial Intelligence
- Luxar: Gaussian splatting for microscopy and scalable interactive web visualisation of multidimensional scientific data
- Optimizing an Automated Processing Pipeline for Regional Macromolecular Proton Fraction and Volume Measurements in the Brain
BibTeX
@misc{laiton20263dmaestro,
title = {{3D-MAESTRO: A scalable, modular, portable pipeline for automated processing of large-scale volumetric brain microscopy data}},
author = {C. Laiton and N. Lusk and Y. Browning and M. Summers and M. Taormina and D. Wang and J. Siegle and H. Myers and B. Tan and P. Kosillo and E. Peterson and D. Toglia and A. Lakunina and S. Burckhardt and J. Young and M. Kapoor and T. Wang and J. Rohde and G. Lynch and S. Yao and S. Narayan and M. Hooper and S. Way and J. Waters and B. Tasic and J. Chandrashekar and A. Glaser and D. Feng and S. Seshamani and K. Svoboda},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.09.750494},
url = {https://www.biorxiv.org/content/10.64898/2026.09.09.750494v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - 3D-MAESTRO: A scalable, modular, portable pipeline for automated processing of large-scale volumetric brain microscopy data
AU - C. Laiton
AU - N. Lusk
AU - Y. Browning
AU - M. Summers
AU - M. Taormina
AU - D. Wang
AU - J. Siegle
AU - H. Myers
AU - B. Tan
AU - P. Kosillo
AU - E. Peterson
AU - D. Toglia
AU - A. Lakunina
AU - S. Burckhardt
AU - J. Young
AU - M. Kapoor
AU - T. Wang
AU - J. Rohde
AU - G. Lynch
AU - S. Yao
AU - S. Narayan
AU - M. Hooper
AU - S. Way
AU - J. Waters
AU - B. Tasic
AU - J. Chandrashekar
AU - A. Glaser
AU - D. Feng
AU - S. Seshamani
AU - K. Svoboda
PY - 2026
DA - 2026/09/09
PB - bioRxiv
DO - 10.64898/2026.09.09.750494
UR - https://www.biorxiv.org/content/10.64898/2026.09.09.750494v1
AB - 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.
ER -