Open Chrono-Morph Viewer: visualize big bioimage time series containing heterogeneous volumes

Area of Science:

• Bioimaging and Computational Biology
• Scientific Software Development

Background:

• Time-lapse 3D imaging is crucial for biological process studies but demands software capable of managing terabytes of voxel data.
• Existing multidimensional viewers often struggle with heterogeneous voxel counts, datatypes, and modalities within a single timeline.

Purpose of the Study:

• To introduce Open Chrono-Morph Viewer (OCMV), a software solution for efficient investigation of complex biological imaging datasets.
• To provide a user-friendly interface for handling multi-timescale and heterogeneous data, overcoming limitations of current tools.

Main Methods:

• Development of OCMV with a straightforward graphical user interface (GUI).
• Utilizes the common NRRD format for compatibility and supports separate volume files for multi-timescale datasets.
• Incorporates dynamic clipping surfaces for 3D morphology investigation and a scriptable animation API for reproducible visualization.

Main Results:

• OCMV facilitates rapid investigation of large, multi-timescale biological datasets.
• The software supports heterogeneous voxel counts, datatypes, and modalities in a unified timeline.
• Enables quantitative, repeatable, and publication-quality visualizations through its animation API.

Conclusions:

• OCMV offers a robust and accessible solution for advanced bioimaging data analysis.
• Its design promotes community-driven development through implementation in pure Python with common libraries.
• The software enhances the study of biological processes by simplifying the handling and visualization of complex imaging data.