Abstract
Fluorescence molecular tomography (FMT), as a promising imaging modality, can three-dimensionally locate the specific tumor position in small animals. However, it remains challenging for effective and robust reconstruction of fluorescent probe distribution in animals. In this paper, we present a novel method based on sparsity adaptive subspace pursuit (SASP) for FMT reconstruction. Some innovative strategies including subspace projection, the bottom-up sparsity adaptive approach, and backtracking technique are associated with the SASP method, which guarantees the accuracy, efficiency, and robustness for FMT reconstruction. Three numerical experiments based on a mouse-mimicking heterogeneous phantom have been performed to validate the feasibility of the SASP method. The results show that the proposed SASP method can achieve satisfactory source localization with a bias less than 1mm; the efficiency of the method is much faster than mainstream reconstruction methods; and this approach is robust even under quite ill-posed condition. Furthermore, we have applied this method to an in vivo mouse model, and the results demonstrate the feasibility of the practical FMT application with the SASP method.
Highlights
With the solid development of fluorescent probes and reporter technologies [1], the application of fluorescence molecular imaging in biomedical study has become a hot spot over the past few years [2, 3]
It is challenging for Fluorescence molecular tomography (FMT) to reconstruct the fluorescence biodistribution effectively and robustly [6], because FMT presents a challenging inverse problem which is quite ill-posed or ill-conditioned due to the following three reasons [6, 7]: 1. Photons emitted from the fluorescent sources undergo multiple scattering and potential absorption in biological tissues
A new sparse reconstruction problem, with a greatly reduced order compared to the original optimization problem is formed between the measurement data sets and the permissible coefficients
Summary
With the solid development of fluorescent probes and reporter technologies [1], the application of fluorescence molecular imaging in biomedical study has become a hot spot over the past few years [2, 3]. To preserve the sparsity of the fluorescent sources, an iteratively reweighted scheme based approach, which was able to obtain more reasonable and satisfactory results compared with the Tikhonov method was proposed [14]. To improve the reconstruction accuracy, an effective FMT reconstruction algorithm based on the iterated shrinkage method with the L1-norm (IS_L1) was proposed [15], the reconstruction algorithm was able to comparatively acquire accurate results even with quite limited measurement data sets. #200134 - $15.00 USD Received 25 Oct 2013; revised 25 Dec 2013; accepted 27 Dec 2013; published 8 Jan 2014 convergence rate of this algorithm is linear since it is a first-order method [16] It needs a large number of iterations to reach an acceptable solution, especially when the dimension of the FMT inverse problem is quite large.
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