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UELer

Usability Enhanced Linked Viewer — a Jupyter Notebook-integrated viewer for MIBI images with linked interactive plots and enhanced usability.

Binder GitHub

What is UELer?

UELer is an interactive image viewer designed for multiplexed imaging data (MIBI, IMC, and similar technologies). It runs directly inside Jupyter notebooks and provides:

  • Linked, interactive visualizations — scatter plots, heatmaps, and gallery views are synchronized with the spatial image display.
  • Multi-channel rendering — visualize and compare channels with per-channel color and contrast controls.
  • Segmentation overlays — view and paint cell segmentation masks, annotation overlays, and custom color sets.
  • ROI Manager — capture, label, and export regions of interest with persistent storage.
  • Batch export — export full FOVs, ROIs, and single-cell crops to PNG or PDF, with optional scale bars and overlays.
  • Map mode — stitch multiple FOVs into a single spatial overview with full interactive navigation.
  • OME-TIFF support — load and render OME-TIFF files alongside standard TIFF directories.

Try It Without Installation

You can launch UELer in your browser via Binder — no local setup required:

Binder

Quick Navigation

  • Installation

    Set up UELer using micromamba and pip.

  • Get Started

    Configure and launch your first viewer session.

  • Tutorials

    Step-by-step guides for core features.

  • FAQ

    Answers to common questions.

  • Developer Notes

    Architecture notes and design decisions.

Supported Data Formats

Format Description
TIFF directory Standard per-channel TIFFs organized in <base_folder>/<fov>/
OME-TIFF Multi-channel OME-TIFF files with embedded metadata
CSV cell table Per-cell feature tables (e.g., from ark-analysis)
Segmentation masks Single-channel TIFF rasters for cell segmentation
Annotation masks Per-class TIFF rasters for region annotation

License

UELer is released under the GPL-3.0 license.