EPFL | Biomedical Imaging Group

Sparsity-Driven Reconstruction for FDOT with Anatomical Priors

J.-C. Baritaux, K. Hassler, M. Bucher, S. Sanyal, M. Unser

IEEE Transactions on Medical Imaging, vol. 30, no. 5, pp. 1143–1153, May 2011.

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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AUTHOR="Baritaux, J.-C. and Hassler, K. and Bucher, M. and Sanyal, S.
	and Unser, M.",
TITLE="Sparsity-Driven Reconstruction for {FDOT} with Anatomical
	Priors",
JOURNAL="{IEEE} Transactions on Medical Imaging",
YEAR="2011",
volume="30",
number="5",
pages="1143--1153",
month="May",
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