3Dm DATA MANAGEMENT

3Dm turns large 3D tissue imaging data into analysis ready volumes.

Process whole tissue imaging datasets with automated stitching, registration, correction, and multi-channel integration for digital pathology, spatial profiling, and quantitative tissue analysis.

FROM RAW DATA TO ANALYSIS READY VOLUMES

3Dm prepares volumetric datasets for the next step in spatial biology.

Large-scale 3D tissue imaging creates complex multi-channel data. 3Dm brings those image volumes into a cleaner, aligned, and structured format so teams can move from acquisition to digital pathology, spatial profiling, and AI-powered analysis.

The goal is simple: reduce manual processing burden while preserving the quality needed for quantitative tissue analysis.

01

Capture

Start with large 3D tissue imaging datasets generated from intact samples and multi-channel fluorescence imaging.

02

Stitch and align

Assemble tiles and align image volumes to create coherent whole tissue imaging datasets.

03

Correct artifacts

Apply image correction steps such as flat-field correction and destriping to improve dataset consistency.

04

Integrate channels

Register fluorescence channels so spatial relationships can be evaluated across tissue architecture.

05

Prepare for 3Dai

Move analysis ready volumetric datasets into downstream AI-powered analysis and quantitative tissue analysis workflows.

Core processing capabilities

Correct, align, and structure 3D image volumes before analysis.

3Dm helps turn large whole tissue imaging data into cleaner, registered volumetric datasets for digital pathology, spatial profiling, and quantitative tissue analysis.

Stitching and alignment preview for 3D tissue imaging data
01

Precise alignment

Stitch and align images after acquisition to build coherent large-scale 3D tissue imaging datasets from intact samples.

Flat-field correction preview showing improved illumination consistency
02

Uniform illumination

Apply flat-field correction to reduce uneven brightness across the imaging field and improve dataset consistency.

03

Destriping

Reduce stripe artifacts from uneven illumination or shadows to improve visual consistency across large 3D tissue imaging volumes.

04

Multi-channel integration

Register fluorescence channels so marker relationships can be interpreted across intact tissue architecture and analysis ready volumetric datasets.

Built for large 3D datasets

Manage the data complexity behind whole tissue imaging.

Large-scale 3D tissue imaging produces volumetric datasets that need more than storage. They need correction, registration, organization, and preparation before reliable spatial profiling or AI-powered analysis can begin.

3Dm connects image acquisition to interpretation. It supports the transition from raw imaging data to cleaner, structured datasets that can move into downstream digital pathology and quantitative tissue analysis workflows.

1

Complex input

Large multi-channel image data from intact tissue samples, captured as volumetric datasets.

2

Processing layer

Stitching, alignment, correction, destriping, and channel registration help standardize the image volume.

3

Analysis ready output

Cleaner and structured data supports downstream visualization, spatial profiling, and quantitative tissue analysis.

Volumetric datasets Registered channels Digital pathology AI-powered analysis

Applications

Data management for research programs that depend on clean 3D image volumes.

3Dm supports 3D tissue imaging workflows where image quality, channel registration, and dataset consistency matter before downstream interpretation.

Drug discovery

Prepare large 3D imaging datasets for analysis of tissue architecture, marker distribution, and spatial relationships in translational research workflows.

  • Whole tissue imaging datasets
  • Multi-channel fluorescence data
  • Analysis-ready volumetric outputs

Clinical research

Improve consistency across processed image volumes so digital pathology and spatial profiling teams can evaluate intact tissue context.

  • Registered tissue volumes
  • Cleaner image data for review
  • Support for quantitative tissue analysis

Biomarker discovery

Structure large imaging data before downstream analysis so spatial patterns can be evaluated across intact 3D tissue architecture.

  • Spatial profiling workflows
  • Channel-aware marker context
  • Preparation for AI-powered analysis

In the Aurora 3D Spatial Biology Solution, 3Dm sits between 3Di image acquisition and 3Dai AI-powered analysis.

Bridge from image to insight