Video In Vivo Toolbox

The tool ingests a video from the user's dataset and analyzes a defined temporal window to compute core imaging metrics. It supports optional ROI definitions and multiple analysis modes, including brightness, motion, and ROI-based intensities. Outputs include duration, frame rate, and per-ROI statistics, enabling consistent reporting across experiments. It is designed for in vivo research workflows where controlled timing and region of interest must be measured across videos for comparison or QA.

Under the hood, the tool reads frames, converts to a consistent color space, and computes luminance-based metrics. Motion is quantified via frame-to-frame differences normalized by frame count. If fluorescence channels are present, channel-specific intensities are calculated within each ROI. Validation checks ensure start_time and end_time define a valid window, and ROI coordinates lie inside frame bounds. Missing data or unsupported codecs produce structured error signals rather than UI prompts.

Beneficiaries include imaging core facilities, bioengineering labs, and researchers performing longitudinal in vivo studies. The tool provides repeatable metrics, audit trails, and straightforward export options, reducing manual calculations and enabling cross-study comparisons.

Unique value arises from in vivo-oriented ROI support, robust handling of common biomedical video formats, and a compact JSON report suitable for automated pipelines.