ARACAM: A RGB-D Multi-View Photogrammetry System for Lower Limb 3D Reconstruction Applications.

Area of Science:

• Biomedical Engineering
• Computer Vision
• Prosthetics and Orthotics

Background:

• Rising global amputations, particularly from diabetic foot complications, necessitate advanced lower limb prostheses.
• Traditional handcrafted prosthesis fabrication is being enhanced by integrating new technologies for improved functionality and comfort.
• Computer vision and 3D reconstruction offer promising avenues for optimizing prosthetic design.

Purpose of the Study:

• To design, prototype, and validate a functional 3D scanning system for plaster cast molds.
• To establish a platform for future lower limb prosthesis reconstruction technologies.
• To evaluate the system's accuracy and competitiveness against existing methods.

Main Methods:

• Utilized an image capture system with 5 stereoscopic cameras and 4 DOF mountings.
• Developed algorithms for camera calibration, image segmentation, registration, and surface reconstruction.
• Tested the system on plaster cast molds and a 3D printed model derived from CT scans.

Main Results:

• Segmentation achieved an average similarity of 87% (Dice coefficient) and an average error of 6.40 mm (Hausdorff distance) for plaster casts.
• Testing on a 3D printed model showed an average Hausdorff distance error of ≤1.93 mm.
• The system demonstrated competitive accuracy compared to state-of-the-art methods.

Conclusions:

• The developed 3D scanning system is a functional and accurate tool for capturing plaster cast molds.
• This technology provides a viable platform for advancing lower limb prosthesis design and fabrication.
• The system's accuracy makes it a competitive solution in the field of prosthetic reconstruction.