Development of augmented reality training simulator systems for neurosurgery using model-driven software engineering

Hamza Ghandorh, Justin Mackenzie and Roy Eagleson

Electrical and Computer Engineering, 2017 IEEE 30th Canadian Conference on Electrical and Computer Engineering (CCECE)


Neurosurgical procedures are complicated processes, providing challenges and demands ranging from medical knowledge and judgment to the neurosurgeons dexterity and perceptual capacities. Deliberate training of common neurosurgical procedures and underlying tasks is extremely important. One effective method for the training is to enhance the required surgical training tasks through the use of neurosurgical simulators. Development of neurosurgical simulators is challenging due to many reasons. In this work, we proposed to facilitate the development of new augmented reality neurosurgical simulator systems through the adoption of model-driven engineering. Our developed systems involve the interactive visualization of three-dimension brain meshes in order to train users and simulate a targeting task towards a variety of predetermined virtual targets. We present our results in a way which highlights two new design artifacts through our MDE approach.