Dr. Zeyu Liu Profile

Dr. Zeyu Liu

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Proceedings Article | 29 December 2022 Open Access

Multi-attention prior based residual encoder-decoder network for fast and accurate reconstruction in fluorescence molecular tomography

Peng Zhang, Fan Song, Chenbin Ma, Zeyu Liu, Guanglei Zhang

Proceedings Volume 12506, 125063F (2022) https://doi.org/10.1117/12.2662505

KEYWORDS: Reconstruction algorithms, Inverse problems, Fluorescence tomography, Tumors, Tomography, Tissues, Photons, Convolution, Scattering

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Fluorescence molecular tomography (FMT) is a powerful modality for resolving the three-dimensional (3D) distribution of fluorescent targets inside biological tissues. However, the inverse problem of the FMT is severely ill-posed due to the strong scattering effects of photons inside biological tissues. Previously, regularization-based methods have been widely used to mitigate the ill-posedness of FMT. Due to the complex iterative computation and time-consuming reconstruction process, the FMT remains an intractable challenge for achieving accurate and fast 3D reconstructions. In this work, we propose a multi-attention prior based residual encoder-decoder network (MAP-REDN) to perform FMT reconstruction. Firstly, the multi-attention mechanism can provide weighted a priori information to the fluorescence source, enabling MAP-REDN to effectively mitigate the ill-posedness and enhance the reconstruction accuracy. Secondly, since the direct reconstruction strategy is adopted, the complex iterative computation process in the traditional regularization-based algorithms can be avoided, thus tremendously accelerating the reconstruction process. The experimental results demonstrate the feasibility of the MAP-REDN in achieving accurate and fast FMT reconstruction.

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