Data Entry: Please note that the research database will be replaced by UNIverse by the end of October 2023. Please enter your data into the system https://universe-intern.unibas.ch. Thanks
A bilinear model for temporally coherent respiratory motion
Editor(s)
Workshop on Abdominal Imaging: Computational Challenges and Clinical Applications
Book title (Conference Proceedings)
Abdominal imaging : computational and clinical applications ; 6th international workshop, ABDI 2014, held in conjunction with MICCAI 2014, Cambridge, MA, USA, September 14, 2014
Volume
8676
Place of Conference
MICCAI , Cambridge, MA, USA
Year of Conference
2014
Publisher
Springer
Place of Publication
Cham
Pages
S. 221-228
Abstract
We propose a bilinear model of respiratory organ motion. The advantages of classical statistical shape modelling are combined with a preconditioned trajectory basis for separately modelling the shape and motion components of the data. The separation of a linear basis into bilinear form leads to a more compact representation of the underlying physical process and the resulting model respects the temporal regularity within the training data, which is an important property for modelling quasi-periodic data. Bilinear modelling is combined with a Bayesian reconstruction algorithm for sparse data under observation noise. By applying the model to liver motion data, we show that our bilinear formulation of respiratory motion is significantly more parsimonious and can even outperform linear PCA-based models.
