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    Project 10 · Case study

    Software for 3D-Printed Organ Regeneration Research

    Syto Studio: the HMI researchers used to 3D-print tissue constructs for organ regeneration studies. React, Flask, Klipper/Moonraker, OpenCV.

    ReactFlaskPythonOpenCVMoonraker APIWebSocketComputer VisionAutomated Calibration
    Software for 3D-Printed Organ Regeneration Research - Create Protocol

    Create Protocol — 1 of 3

    Case study

    The problem

    Biomedical researchers needed a control interface for custom 3D bioprinters: protocol authoring, live printer monitoring, automated calibration, real-time print quality checks. Existing tools were built for hobbyist FDM printers and didn't fit a research lab's workflow.

    The approach

    React frontend, Flask backend. Klipper API for STL handling, slicing, and temperature control. Moonraker for live printer state. OpenCV for vision-based quality control, catching dropped layers, nozzle drift, and calibration failures while the print was still running. I built the protocol-authoring layer specifically around how the researchers actually described their work, not around how printer firmware wanted to receive it.

    What worked

    Researchers used the system to 3D-print tissue constructs that went into living animals for organ regeneration studies. Setup time dropped around 30%. Print accuracy improved meaningfully once the vision pipeline was catching early failures.

    What I'd do differently

    Early versions of the vision pipeline ran too hot on latency. I should have started with a simpler frame-skip heuristic before reaching for full OpenCV processing per frame.

    More detail

    A control interface for custom biomedical 3D printers. Handled protocol authoring, live printer monitoring, automated calibration, and real-time vision-based quality control. The researchers who used this printed tissue constructs that went into living animals for organ regeneration studies.