Abstract
Dynamic fluorescence molecular tomography (FMT) plays an important role in drug delivery research. However, the majority of current reconstruction methods focus on solving the stationary FMT problems. If the stationary reconstruction methods are applied to the time-varying fluorescence measurements, the reconstructed results may suffer from a high level of artifacts. In addition, based on the stationary methods, only one tomographic image can be obtained after scanning one circle projection data. As a result, the movement of fluorophore in imaged object may not be detected due to the relative long data acquisition time (typically >1 min). In this paper, we apply extended kalman filter (EKF) technique to solve the non-stationary fluorescence tomography problem. Especially, to improve the EKF reconstruction performance, the generalized inverse of kalman gain is calculated by a second-order iterative method. The numerical simulation, phantom, and in vivo experiments are performed to evaluate the performance of the method. The experimental results indicate that by using the proposed EKF-based second-order iterative (EKF-SOI) method, we cannot only clearly resolve the time-varying distributions of fluorophore within imaged object, but also greatly improve the reconstruction time resolution (~2.5 sec/frame) which makes it possible to detect the movement of fluorophore during the imaging processes.
Highlights
Dynamic fluorescence molecular tomography (FMT) is important for bio-medical research since it allows non-invasive, tomographic imaging of the dynamic bio-distributions of fluorescent bio-markers within small animals in vivo [1,2,3]
Dynamic FMT imaging allows fast and non-invasively resolving the 3-D distribution of fluorescence bio-markers within small animal in vivo, which is helpful for bio-medical research
The main reason is that the current reconstruction methods are performed based on the implicit assumption that the fluorophore's distributions are stationary during FMT imaging processes
Summary
Dynamic fluorescence molecular tomography (FMT) is important for bio-medical research since it allows non-invasive, tomographic imaging of the dynamic bio-distributions of fluorescent bio-markers within small animals in vivo [1,2,3]. The main reason is the current reconstruction methods [6,7,8,9] mainly focus on solving the stationary FMT tomographic problems. They are performed based on the (implicit) assumption that the fluorophore is stationary that it does not change during FMT imaging processes. The imaging time is needed to collect a complete set of measurements, which will be used as input data of the conventional reconstruction methods. In some applications, e.g., the drug delivery research, the fluorophore's concentration and location may change significantly when collecting these projection data. The above factors limit the widespread application of dynamic FMT in bio-medical research
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