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Sparsity-Driven Reconstruction for FDOT With Anatomical Priors

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5 Author(s)
Baritaux, J.-C. ; Swiss Fed. Inst. of Technol. of Lausanne, Lausanne, Switzerland ; Hassler, K. ; Bucher, M. ; Sanyal, S.
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In 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 ℓ1-norm penalization and total variation penalization. Results on synthetic and experimental data are presented.

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Medical Imaging, IEEE Transactions on  (Volume:30 ,  Issue: 5 )