How can we apply lessons learned from adaptation for CFD and Nuclear femtography to meshing for medical images ? In particular, in the case of non rigid registration for medical images one could re-use the ideas of error-based metric construction in order to create metric than can reduce the registration error.
Related papers
- N. Chrisochoides,
Y. Liu,
F. Drakopoulos,
A. Kot,
P. Foteinos,
C. Tsolakis ,
E. Billias,
O. Clatz,
N. Ayache,
A. Fedorov,
A. Golby,
P. Black,
R. Kikinis,"Comparison of physics-based deformable registration methods for image-guided neurosurgery,"Frontiers in Digital Health,
2023
- F. Drakopoulos,
C. Tsolakis ,
A. Angelopoulos,
Y. Liu,
C. Yao,
K. Kavazidi,
N. Foroglou,
A. Fedorov,
S. Frisken,
R. Kikinis,
A. Golby,
N. Chrisochoides,"Adaptive physics-based non-rigid registration for immersive image-guided neuronavigation systems,"Frontiers in Digital Health,
vol. 2,
pp. 66,
2020