Efficient Meta-modelling for the simulation of soft tissue deformations

This work has been done as a part of scientific deliverable 4.1 of ITN Rainbow.(https://rainbow.ku.dk).

A. In first part program is written for predicting the position of brain tumour in brain surgery. In the surgery, as surgeonmakes incision and opens the skull, the brain tumour relocates under new boundary conditions. Predicting the position of tumor under different incision sizes is invaluable data for surgeons, which is done by using gaussian process regressor meta-model. 

B. Second part shows the potential of deep learning approach to solve non-linear deformation behaviour of a cantilever beam in real time constraints. It is shown that deep learning model is able to predict the solution in a very less time compared to finite element solution time and yet maintaining the reasonable accuracy.