Integrated Modeling and Reconstruction with Sparsity Constraints for fDOT

We present a numerical framework for Fluorescence Diffuse Optical Tomography (fDOT) that combines a forward model together with an iterative reconstruction procedure. Using rapid linear solvers, we derived an efficient reconstruction strategy for quadratic regularizers. The method outperforms traditional reconstruction approaches. Starting from quadradic regularization, we then extend the framework to more general $ L _{ p } $ constraints. We present reconstruction experiments that confirm the superiority of non-quadratic sparsity promoting regularization.


Published in:
Proceedings of the Sixth IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI'09), Boston MA, USA, 173–176
Year:
2009
Publisher:
IEEE
Laboratories:




 Record created 2015-09-18, last modified 2018-01-28

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

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