3D Human-Body Modeling for Medical Simulation: Usability and Robustness of Photogrammetry Techniques

Total skin electron therapy TSET is mainly used in the treatment of mycosis fungoides, a rare cutaneous T-cell lymphoma affecting the first few millimeters of skin. The Skinscan project aims to optimize irradiation by creating a 3D model of the patient’s body surface. This would avoid overdosing or underdosing in different skin areas compared to the prescribed dose and would reduce the inhomogeneity of dose distribution associated with current techniques used during TSET therapy. In SkinScan, we investigate the creation of 3D models of the human body, analyzing the compromise between usability of the software and robustness of the techniques. State-of-the-art techniques for the creation of the 3D models are RGBD and photogrammetry. The first ones require dedicated devices, the other are based on standard photographs. Commercial software to align the different views and to create the models are available, and they can be used by non-experts. The final application would indeed require the creation of ad-hoc models for a personalized medical intervention on the patients. Such models should be created in hospitals, without the intervention of computer scientists. Moreover, accurate 3D modeling often requires specific post-processing to remove noise without adding artifacts on the surfaces. We present the preliminary results to create the 3D models to be used as the input of the SkinScan simulation pipeline. We modeled a flat wall and a box composed of flat surfaces, to evaluate the amount of noise in the 3D reconstruction and the pre-processing of the images to remove it. We then modeled two different body parts, a hand and a shoulder, with the aim of understanding the best compromise between the accuracy of the model and its size, thus the simulation time.