An Efficient Numerical Method for General L Regularization in Fluorescence Molecular Tomography

• Published in: IEEE transactions on medical imaging Vol. 29; no. 4; pp. 1075 - 1087
• Main Authors: Baritaux, J.-C., Hassler, K., Unser, M.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.04.2010
• Subjects: Algorithms; Biomedical optical imaging; Bones; Fluorescence; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image reconstruction; Imaging, Three-Dimensional - methods; Iterative methods; Microscopy, Fluorescence - methods; Molecular biophysics; Molecular Probe Techniques; Optical imaging; Optical scattering; optical tomography; Pattern Recognition, Automated - methods; Probes; Reproducibility of Results; Sensitivity and Specificity; Tomography; Tomography, Optical - methods
• ISSN: 0278-0062; 1558-254X; 1558-254X
• DOI: 10.1109/TMI.2010.2042814

Reconstruction algorithms for fluorescence tomography have to address two crucial issues: 1) the ill-posedness of the reconstruction problem, 2) the large scale of numerical problems arising from imaging of 3-D samples. Our contribution is the design and implementation of a reconstruction algorithm that incorporates general Lp regularization ( p ¿ 1). The originality of this work lies in the application of general Lp constraints to fluorescence tomography, combined with an efficient matrix-free strategy that enables the algorithm to deal with large reconstruction problems at reduced memory and computational costs. In the experimental part, we specialize the application of the algorithm to the case of sparsity promoting constraints ( L 1 ). We validate the adequacy of L 1 regularization for the investigation of phenomena that are well described by a sparse model, using data acquired during phantom experiments.