Abstract
As a novel modality of molecular imaging, bioluminescence tomography (BLT) is used to in vivo observe and measure the biological process at cellular and molecular level in small animals. The core issue of BLT is to determine the distribution of internal bioluminescent sources from optical measurements on external surface. In this paper, a new algorithm is presented for BLT source reconstruction based on adaptive hp-finite element method. Using adaptive mesh refinement strategy and intelligent permissible source region, we can obtain more accurate information about the location and density of sources, with the robustness, stability and efficiency improved. Numerical simulations and physical experiment were both conducted to verify the performance of the proposed algorithm, where the optical data on phantom surface were obtained via Monte Carlo simulation and CCD camera detection, respectively. The results represent the merits and potential of our algorithm for BLT source reconstruction.
Highlights
Molecular imaging has rapidly developed over the past few years because of its ability to observe the molecular and cellular information in vivo [1,2,3].Compared with the traditional imaging techniques like positron emission tomography (PET), single photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), ultrasound, X-ray computed tomography (CT), optical imaging modality, especially fluorescence molecular tomography (FMT) and bioluminescence tomography (BLT) methods, has high molecular specificity, nonionizing radiation and high cost-effectiveness [4,5,6]
Feng et al brought forward an optimal permissible source region strategy which is automatically selected without human intervention [12]
We develop a new algorithm for source reconstruction based on adaptive hp-finite element method in BLT
Summary
Molecular imaging has rapidly developed over the past few years because of its ability to observe the molecular and cellular information in vivo [1,2,3].Compared with the traditional imaging techniques like positron emission tomography (PET), single photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), ultrasound, X-ray computed tomography (CT), optical imaging modality, especially fluorescence molecular tomography (FMT) and bioluminescence tomography (BLT) methods, has high molecular specificity, nonionizing radiation and high cost-effectiveness [4,5,6]. The major advantage of BLT over FMT is that there is no inherent background bioluminescence in most tissues, which yields higher imaging contrast [1]. It becomes an increasingly important instrument for biomedical researchers to diagnose diseases, evaluate therapies, and facilitate drug development with small animals such as mouse models [1,2,3]. The commonly used a priori information includes the optical parameters, the structure of small animals and the permissible source region. A priori permissible source region can be estimated by the surface photon flux distribution and the heterogeneous structure of the detected object [11]. Feng et al brought forward an optimal permissible source region strategy which is automatically selected without human intervention [12]
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