Data model
Images, annotations, metadata, and analysis stay together.
The platform is designed for scientific datasets where raw pixels are only one part of the research record.
BisQue
Scientific image informatics for reproducible computer vision.
BisQue is the lab’s scientific image platform: a browser-based environment for storing, searching, annotating, visualizing, and analyzing scientific images with extensible modules and flexible metadata.
5D image data Flexible metadata Analysis modules Browser visualization
Scale
Large 5D image data can be handled through web infrastructure.
The public repository describes PB-scale image management, millions of annotations, and large image processing.
Translation
New methods can move from paper to shared analysis module.
BisQue gives domain researchers access to machine-learning tools without requiring them to rebuild the computational stack.
Workshop evidence
BisQue turns scientific image work into browser-visible infrastructure.
The Winter 2025 workshop material makes the product story concrete: large mosaics, multidimensional viewers, containerized workflows, and module outputs can sit inside one shared image-informatics workspace.
Scale
Large mosaics stay inspectable in the web browser.
The workshop shows a 90K by 90K image mosaic in BisQue, making scale a product capability rather than an offline preprocessing footnote.
Materials science
Modules can be stitched into containerized workflows.
EBSD and microstructure workflows become repeatable analysis paths with visible inputs, module steps, and derived outputs.
Bioimaging
Image modules return masks, metadata, and tables together.
Cell segmentation outputs stay connected to image viewers and table inspection, which is the practical base for reproducible bioimage analysis.
Platform capabilities
A scientific image platform built for more than file hosting.
BisQue’s value is the combination of storage, metadata, visualization, annotations, and executable modules. That combination is what lets computer vision research become a reproducible scientific workflow instead of an isolated notebook.
5D scientific images
BisQue is described as a web platform for organizing and quantitatively analyzing up to 5D image data.
Flexible metadata
The platform's metadata facility and open web architecture let researchers create, develop, and share multimodal analyses.
Scalable storage
The public README describes cloud scalability for PB-scale images, millions of annotations, distributed storage, and large 5D images.
Analysis modules
Researchers can extend BisQue with modules that run image analysis in MATLAB, Python, Java, and ImageJ-oriented workflows.
Cross-domain research
The platform has been used across biomedical sciences, neuroscience, wildlife conservation, marine science, and materials science.
Browser access
Research Outreach describes cloud-based analytics that make analysis tools available through a web browser with light client requirements.
Connected research
Published lab systems reuse the same image-informatics foundation.
MethaneMapper and WildlifeMapper expose BisQue dataset visualization links in their repositories. EBSD Superresolution and Time-lapse 3D Cell Analysis describe BisQue module paths for inference. The clinical neuroimaging papers extend the same lab pattern into MRI tumor segmentation, CT segmentation, and connectome-aware analysis.
MethaneMapper Hyperspectral remote sensing CVPR 2023 Highlight WildlifeMapper Ecological computer vision CVPR 2024 EBSD Superresolution Materials microscopy npj Computational Materials 2022 MRI Brain Tumor Segmentation Clinical neuroimaging Frontiers in Neuroscience 2020 Normal Pressure Hydrocephalus Clinical neuroimage analysis BME Frontiers 2022 Time-lapse 3D Cell Analysis Bioimage analysis Scientific Reports 2023
Next layer
BisQue organizes scientific resources. BisQue Ultra turns them into durable AI work.
Ultra can connect to BisQue, then adds a modern resource browser, multidimensional viewers, a React workbench, Go control plane, durable Postgres and NATS JetStream state, Deep Agents workers, gated model training, and OpenAI-compatible model routing.
Extend the platform
Connect a new dataset, analysis module, or scientific workflow.
We work with teams that need shared image infrastructure, browser-visible analysis, or a durable path from BisQue resources into BisQue Ultra.
Primary sources