Orbital Prosthesis Rehabilitation in Biomedical Engineering by Means of Computer Vision-Photogrammetry and 3D Prototyping

Abstract

Eye loss may be caused as a result of eye trauma, accidents, or malignant tumors, which leads the patient to undergo surgery to remove the damaged parts. This research examines the potential of computer vision represented by Structure from Motion (SfM) photogrammetry in fabricating the orbital prosthesis as a noninvasive and low-cost technique. A low-cost camera was used to collect the data towards extracting the dense 3D data of the patient facial features following Structure from Motion-Multi View Stereo (SfM-MVS) algorithms. To restore the defective orbital, a Reverse Engineering (RE) based approach has been applied using the similarity RE algorithms based on the opposite healthy eye to rehabilitate the defected orbital precisely. Following quality assurance and best-fitting statistical analysis, the digital model of the restored eye was converted into a physical model using 3D prototyping. This is later used to fabricate the mold for casting medical-grade silicone to obtain the final orbital prosthesis. The results show the power of SfM photogrammetry by offering a high-accuracy model of 0.048 mm and 0.186 mm relative errors acquired in the horizontal and vertical directions, respectively. These results boost the RE implementation in medicine to reconstruct the patient's damaged eye by mirroring the image of the healthy eye using RE algorithms. Therefore, the margin matching results claim perfect data capture settings and successful data processing workflow as designed in the first place. Consequently, one can claim this approach effectively rehabilitates maxillofacial deformities as an alternative to invasive restoration approaches. The presented approach provided a low-cost and safe workflow that avoids the patient the risks of exposure to harmful rays or magnetic fields available in other sensors.