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Related Experiment Video

Updated: Jun 24, 2026

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

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Published on: April 10, 2016

ScopeViewer: A Browser-Based Solution for Visualizing Large Biological Images.

Danni Luo¹, Sophie Robertson², Yuanchun Zhan¹

¹Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, UT Southwestern Medical Center.

|June 22, 2026

Summary

This summary is machine-generated.

ScopeViewer is a new browser-based software that simplifies visualizing complex spatial transcriptomics (ST) and pathology image data. It provides secure, high-resolution, and interactive exploration of molecular and image features.

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Area of Science:

Bioinformatics
Computational Biology
Medical Imaging

Background:

Spatial transcriptomics (ST) offers high-resolution molecular analysis within tissue contexts.
Visualizing large ST datasets with molecular information presents significant handling and sharing challenges.

Purpose of the Study:

To introduce ScopeViewer, a novel browser-based software solution.
To address the complexities of visualizing and sharing large-scale spatial transcriptomics and pathology image data.

Main Methods:

Developed a browser-based software application, ScopeViewer.
Implemented functionalities for visualizing large image data at multiple zoom levels.
Enabled dual interactive viewing of images and annotations.
Optimized bandwidth for displaying spatial molecular features.
Designed to circumvent data transfers for enhanced security.

Main Results:

ScopeViewer effectively visualizes large image data with annotations at various zoom levels.
Dual interactive viewing provides comprehensive contextual understanding.
Optimized bandwidth ensures a smooth user experience for spatial molecular features.
The software bolsters data security by avoiding direct data transfers.

Conclusions:

ScopeViewer provides a convenient, powerful, and secure platform for researchers.
It supports high-resolution image visualization, including pathology and spatial transcriptomics data.
The open-source platform encourages community contributions and future enhancements.