Utilizing reflective photons could circumvent the penetration limit of FMT, enabling reconstruction of fluorescence distribution near the surface regard less of the object size and extending its applications to surgical navigation and so on. Therefore, a time-domain reflective fluorescence molecular tomography (TD-rFMT) is proposed. The system excites and detects the emission light from the same angle within a field of view of 5 cm. Because the detected intensities of targets depend strongly on the depth, the reconstruction of targets in deep regions would be evidently affected. Therefore, a fluorescence yield reconstruction method with depth regularization and a weighted separation reconstruction strategy for lifetime are developed to enhance the performance for deep targets. Through simulations and phantom experiments, TD-rFMT is proved capable of reconstructing fluorescence distribution within a 2.5-cm depth with accurate reconstructed yield, lifetime, and target position(s).
For fluorescence molecular tomography, higher spatial resolution can be achieved using minimally scattered early photons. Conventional reconstruction methods of early photon tomography (EPT) are based on the integral of temporal point spread function (TPSF), which may lead to poor image quality due to systematic noise and time mismatch between the TPSF data and forward model. The derivative of the rising portion of TPSF is proposed to be used in EPT to increase the performance of reconstruction because the derivative is less sensitive to noise and time mismatch than the integral. A method based on projected Tikhonov regularization with the reconstructed result of steepest descent algorithm as a priori information is developed. Using the derivative of TPSF, the method can achieve high spatial resolution in phantom experiments and is capable of separating targets with an edge–edge distance of 1.5 mm.
Fluorescence probes have distinct yields and lifetimes when located in different environments, which makes the reconstruction of fluorescence molecular lifetime tomography (FMLT) challenging. To enhance the reconstruction performance of time-domain (TD) FMLT with heterogeneous targets, a self-guided L1 regularization projected steepest descent (SGL1PSD) algorithm is proposed. Different from other algorithms performed in time domain, SGL1PSD introduces a time-resolved strategy into fluorescence yield reconstruction. The algorithm consists of four steps. Step 1 reconstructs the initial yield map with full time gate strategy; steps 2–4 reconstruct the inverse lifetime map, the yield map, and the inverse lifetime map again with time-resolved strategy, respectively. The reconstruction result of each step is used as a priori for the reconstruction of the next step. Projected iterated Tikhonov regularization algorithm is adopted for the yield map reconstructions in steps 1 and 3 to provide a solution with iterative refinement and nonnegative constraint. The inverse lifetime map reconstructions in steps 2 and 4 are based on L1 regularization projected steepest descent algorithm, which employ the L1 regularization to reduce the ill-posedness of the high-dimensional nonlinear problem. Phantom experiments with heterogeneous targets at different edge-to-edge distances demonstrate that SGL1PSD can provide high resolution and quantification accuracy for TD FMLT.
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