Spatio-Temporal Regularization Of Flow-Fields

We introduce a novel variational framework for the regularized reconstruction of time-resolved volumetric flow fields. Our objective functional takes the physical characteristics of the underlying flow into account in both the spatial and the temporal domains. For an efficient minimization of the objective functional, we apply a proximal-splitting algorithm and perform parallel computations. To demonstrate the utility of our variational method, we first denoise a simulated flow-field in the human aorta and show that our method outperforms spatial-only regularization in terms of signal-to-noise ratio (SNR). We then apply the scheme to a real 3D+time phase-contrast MRI dataset and obtain high-quality visualizations.


Published in:
2013 IEEE 10th International Symposium On Biomedical Imaging (ISBI), 836-839
Presented at:
IEEE 10th International Symposium on Biomedical Imaging - From Nano to Macro (ISBI), San Francisco CA, USA, Apr. 07-11, 2013
Year:
2013
Publisher:
New York, IEEE
ISBN:
978-1-4673-6455-3
Keywords:
Laboratories:




 Record created 2014-01-09, last modified 2018-03-17

External links:
Download fulltextURL
Download fulltextURL
Download fulltextURL
Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)