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Related Experiment Video

Updated: May 26, 2025

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

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Robot-Based Procedure for 3D Reconstruction of Abdominal Organs Using the Iterative Closest Point and Pose Graph

Birthe Göbel^1,2, Jonas Huurdeman^2,3, Alexander Reiterer^1,4

¹Department of Sustainable Systems Engineering, NATECH, University of Freiburg, Emmy-Noether-Straße 2, 79110 Freiburg, Germany.

Journal of Imaging

|February 25, 2025

Summary

This summary is machine-generated.

This study presents a robot-based 3D reconstruction method for laparoscopy that eliminates complex hand-eye calibration. Pose optimization algorithms replace manual calibration, enabling efficient image-guided navigation in surgical interventions.

Keywords:

Image-based 3D reconstruction laparoscopy multi-view reconstruction robot-assisted intervention stereo vision

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Area of Science:

Medical Robotics
Surgical Navigation
Computer Vision

Background:

Robot-assisted surgery and image-guided navigation are advancing laparoscopy.
Accurate transformation data between the camera and robot is crucial for image acquisition.
Traditional hand-eye calibration is complex and required after each procedure, posing a challenge for clinical settings.

Purpose of the Study:

To develop a robot-based multi-view 3D reconstruction procedure that bypasses the need for manual hand-eye calibration.
To implement pose optimization algorithms to determine camera-robot transformations.
To enable efficient and accurate 3D reconstruction for minimally invasive surgeries.

Main Methods:

Utilized a robotic arm and stereo laparoscope for image acquisition.
Employed Semi Global Matching (OpenCV) for stereo depth measurement.
Applied multiscale color iterative closest point and multiway registration with pose graph (Open3D) for pose optimization.

Main Results:

Achieved low root mean squared error (1.1-3.37 mm).
Generated dense point clouds for detailed 3D models.
Demonstrated a plausible 3D reconstruction without requiring hand-eye calibration.

Conclusions:

The proposed method offers a viable alternative to complex hand-eye calibration in robot-assisted laparoscopy.
Pose optimization effectively compensates for the lack of manual calibration.
This approach facilitates efficient 3D reconstruction for improved surgical guidance.