An inverse problem approach to the estimation of volume change

Authors:
Martin Schweiger;Oscar Camara-Rey;William R. Crum;Emma Lewis;Julia Schnabel;Simon R. Arridge;Derek L. G. Hill;Nick Fox
Affiliations:
Department of Computer Science, University College London;Centre for Medical Image Computing, University College London;Centre for Medical Image Computing, University College London;Centre for Medical Image Computing, University College London;Centre for Medical Image Computing, University College London;Department of Computer Science, University College London;Centre for Medical Image Computing, University College London;Dementia Research Centre, Institute of Neurology, University College London
Venue:
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Year:
2005

Citing 1
Cited 1

Marching cubes: A high resolution 3D surface construction algorithm

SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques

Towards Regional Elastography of Intracranial Aneurysms

MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present a new technique for determining structure-by-structure volume changes, using an inverse problem approach. Given a pre-labelled brain and a series of images at different time-points, we generate finite element meshes from the image data, with volume change modelled by means of an unknown coefficient of expansion on a perstructure basis. We can then determine the volume change in each structure of interest using inverse problem optimization techniques. The proposed method has been tested with simulated and clinical data. Results suggest that the presented technique can be seen as an alternative for volume change estimation.