"Surgeons are trained as apprentices. Some conditions are rarely encountered and surgeons will only be trained in the specific skills associated with a given situation if they come across it. At the end of their residency, it is hoped that they will have faced sufficiently many cases to be competent. This can be dangerous to the patients.
If we were able to reproduce faithfully, in a virtual environment, the audio, visual and haptic experience of a surgeon as they prod, pull and incise tissue, then, surgeons would not have to train on cadavers, phantoms, or on the patients themselves.
Only a few researchers in the Computational Mechanics community have attacked the mechanical problems related to surgical simulation, so that mechanical faithfulness is not on par with audiovisual. This lack of fidelity in the reproduction of surgical acts such as cutting may explain why most surgeons who tested existing simulators report that the ""sensation"" fed back to them remains unrealistic. To date, the proposers are not aware of Computational Mechanics solutions addressing, at the same time, geometrical faithfulness, material realism, evolving cuts and quality control of the solution.
The measurable objectives for this research are as follows:
O1:Significantly alleviate the mesh generation and regeneration burden to represent organs’ geometries, underlying tissue microstructure and cuts with sufficient accuracy but minimal user intervention
O2:Move away from simplistic coarse-scale material models by deducing tissue rupture at the organ level from constitutive (e.g. damage) and contact models designed at the meso and micro scales
O3:Ensure real-time results through model order reduction coupled with the multi-scale fracture tools of O2
O4:Control solution accuracy and validate against a range of biomechanics problems including real-life brain surgery interventions with the available at our collaborators’"
Fields of science
Call for proposal
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