Affiliation:
1. Tsinghua University
2. Beijing Jiaotong University
3. Chinese Academy of Sciences
4. Beijing Information Science and Technology University
5. Beihang University
Abstract
A time-domain fluorescence molecular tomography in reflective geometry (TD-rFMT) has been proposed to circumvent the penetration limit and reconstruct fluorescence distribution within a 2.5-cm depth regardless of the object size. In this paper, an end-to-end encoder-decoder network is proposed to further enhance the reconstruction performance of TD-rFMT. The network reconstructs both the fluorescence yield and lifetime distributions directly from the time-resolved fluorescent signals. According to the properties of TD-rFMT, proper noise was added to the simulation training data and a customized loss function was adopted for self-supervised and supervised joint training. Simulations and phantom experiments demonstrate that the proposed network can significantly improve the spatial resolution, positioning accuracy, and accuracy of lifetime values.
Funder
National Natural Science Foundation of China
Subject
Atomic and Molecular Physics, and Optics,Biotechnology