Baritaux, Jean-CharlesHassler, KaiBucher, MartinaSanyal, SebantiUnser, Michael2011-12-162011-12-162011-12-16201110.1109/TMI.2011.2136438https://infoscience.epfl.ch/handle/20.500.14299/74152WOS:000290167500012In this paper we propose a method based on (2, 1)-mixed-norm penalization for incorporating a structural prior in FDOT image reconstruction. The effect of (2, 1)-mixed-norm penalization is twofold: first, a sparsifying effect which isolates few anatomical regions where the fluorescent probe has accumulated, and second, a regularization effect inside the selected anatomical regions. After formulating the reconstruction in a variational framework, we analyze the resulting optimization problem and derive a practical numerical method tailored to (2, 1)-mixed-norm regularization. The proposed method includes as particular cases other sparsity promoting regularization methods such as -norm penalization and total variation penalization. Results on synthetic and experimental data are presented.Fluorescence imagingoptical tomographyoptimizationreconstructionDiffuse Optical TomographyIn-VivoFluorescence TomographyMolecular TomographyRegularizationInformationAlgorithmBreasttext::journal::journal article::research article