Intellectual Output 2

Output Title: Creation of Virtual / Augmented Reality Models and International 3D Standardization of Models

Output Type: Learning / Teaching / Training Material – Audiovisual Material

Leading Organisation: Chosun University
Participating Organisations: Hacettepe University

Formation of virtual and augmented reality models of radiologic DICOM data and than producing animated virtual and augmented simulated environments. The 3D data will be given as the same models used for 3D printed physical models. Standardization models will be provided by the way. We will use leap-motion technology, adapted laptop and unity-based system for surgical VR/AR simulators. We will select three main surgical models for this outcome.These models will have measurable outcomes for students who will be educated on.

We will publish the data afterward to determine the efficacy of training modalities. The novel training method with VR/AR based is innovative side of the outcome, however, expected impact of the outcome is to provide effective, anatomy-based, low-cost , technological surgical training method, for decreasing the surgical complications, increasing patient safety and get experience on simulators before the live surgery.

Evaluation of several model's characteristics for standardization. IEEE-EMBS SA 3D Based Medical Application Working Group has working on 3D modeling standards. This outcome will put new comments on 3D modeling, 3D printing of soft and hard tissue standards during the joint meetings of IEEE-EMBS SA and project partners.

The tasks leading to the production of the intellectual output and the applied methodology:
Our groups will operate within the two laboratories of “Modeling and Simulation” and “Computational Visual Design” (formerly CAD-PLM Lab). Current modeling activities related to medical applications are based on novel, highly effective methods for extracting geometric models from 3D medical images at suitable resolution (presently applied to the liver portal system and to nervous cells), as well as on multi-physics simulation and advanced morphometric analysis of the heart cycle. Our project's novel technology for extracting geometric models from 3D medical images has a sound basis in algebraic topology concepts and techniques, as well as and on state-of-the-art methods and algorithms for efficiently handling extremely large and very sparse matrices. This technology has been under development at Roma Tre University from several years now, in collaboration with the Universities of Wisconsin at Madison, of Utah at Salt Lake City and of Texas at Austin. It is currently being applied to the extraction of topologically exact models of neurons and vascular tissue from extreme-resolution microscope images, and to the mapping of neural connections.

We'll plan to evaluate and create standardization on different specifications of the models including Visualize 3D Volume image, Accuracy for Augmented Reality target recognition (the affected part - marker) , Accuracy for Target Recognition (the affected part -marker) tracking, Real-time rendering speed for Target Recognition (the affected part -marker) and 3D objects, Matching level for Target Recognition (the affected part -marker) and 3D objects and Real-time 3D rendering speed for VR simulation etc.