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Only a planar bioluminescence image acquired from an ordinary cooled charge-coupled device (CCD) array every time, how to re-establish the three-dimensional small animal shape and light intensity distribution on the surface has become urgent to be solved as a bottleneck of bioluminescence tomography (BLT) reconstruction. In this paper, a finite element algorithm to solve the Dirichlet type problem...
In this paper, we employ the concept of the Fisher information matrix (FIM) to reformulate and improve on the “Newton's One-Step Error Reconstructor” (NOSER) algorithm. FIM is a systematic approach for incorporating statistical properties of noise, modeling errors and multi-frequency data. The method is discussed in a maximum likelihood estimator (MLE) setting. The ill-posedness of the inverse problem...
Electrical impedance tomography (EIT) offers a possibility of realizing of a low cost and safe modality for clinically monitoring patients being treated with mechanical ventilation. However, image reconstruction algorithm employed at different clinical or research settings varies from one to another, which in turn makes interpretation of regional ventilation across institutions difficult. Seeing the...
The integration of mapping techniques with suitable methods for the characterization and visualization of propagation patterns may enhance the targeting of critical arrhythmic areas, thus optimizing the ablative treatment of atrial arrhythmias. In this study, we tested the feasibility of an innovative approach for the automatic determination of activation and velocity maps from sparse data as provided...
Fluorescence molecular tomography has become a promising technique for in vivo small animal imaging, and has many potential applications. Due to the ill-posed and the ill-conditioned nature of the problem, Tikhonov regularization is generally adopted to stabilize the solution. However, the result is usually over-smoothed. In this study, the sparsity of the fluorescent source is used as a priori information...
The topologically correct and geometrically accurate reconstruction of the cerebral cortex from magnetic resonance (MR) images is an important step in quantitative analysis of the human brain structure, e.g. in cortical thickness measurement studies. Limited resolution of MR images, noise, intensity inhomogeneities, and partial volume effects can all contribute to geometrical inaccuracies and topological...
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