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Single and multi-frame auto-calibration for 3D endoscopy with differential rendering.

Ryo Furukawa, Ryusuke Sagawa, Shiro Oka

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 12, 2023
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel auto-calibration method for 3D endoscopic imaging, improving accuracy in cancer diagnosis and machine learning data annotation. The technique utilizes differential rendering for precise shape recovery without complex initial setups.

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    Area of Science:

    • Medical Imaging
    • Computer Vision
    • Optical Engineering

    Background:

    • 3D measurement in endoscopy aids cancer diagnosis, interventions, and machine learning data annotation.
    • Active stereo systems with pattern projectors and endoscopes are effective but require complex calibration.
    • Endoscope head flexibility limits projector-camera accuracy, necessitating robust auto-calibration.

    Purpose of the Study:

    • To develop a novel auto-calibration method for 3D endoscopic imaging systems.
    • To address the challenge of accurate shape recovery despite projector-camera system complexities and endoscope head movement.
    • To enable practical, one-shot endoscopic depth measurement for clinical applications.

    Main Methods:

    • Proposed a novel auto-calibration method based on differential rendering techniques.
    • Developed a technique to simultaneously estimate the focal length of a diffractive optical element (DOE) and projector-camera extrinsic parameters.
    • Implemented a multi-frame optimization algorithm for joint optimization of intrinsic/extrinsic parameters, frame poses, and shape.

    Main Results:

    • Successfully demonstrated a practical auto-calibration method for 3D endoscopic systems.
    • Achieved simultaneous estimation of DOE focal length and extrinsic parameters.
    • Enabled joint optimization of multiple parameters for improved accuracy in shape recovery.

    Conclusions:

    • The proposed differential rendering-based auto-calibration method offers a practical solution for 3D endoscopic measurements.
    • This approach overcomes limitations of traditional calibration methods, enhancing accuracy and usability in clinical settings.
    • Facilitates one-shot endoscopic depth information acquisition, crucial for cancer diagnosis and AI-driven medical applications.