Affiliation:
1. School of Information Science and Technology, Northwest University, Xi’an, Shaanxi 710127, China
2. National and Local Joint Engineering Research Center for Cultural Heritage Digitization, Xi’an, Shaanxi 710127, China
3. School of Computer Science and Engineering, Xi’an University of Technology, Xi’an, Shaanxi 710127, China
Abstract
Čerenkov luminescence tomography (CLT) is a highly sensitive and promising technique for three-dimensional non-invasive detection of radiopharmaceuticals in living organisms. However, the severe photon scattering effect causes ill-posedness of the inverse problem, and the results of CLT reconstruction are still unsatisfactory. In this work, a multi-stage cascade neural network is proposed to improve the performance of CLT reconstruction, which is based on the attention mechanism and introduces a special constraint. The network cascades an inverse sub-network (ISN) and a forward sub-network (FSN), where the ISN extrapolates the distribution of internal Čerenkov sources from the surface photon intensity, and the FSN is used to derive the surface photon intensity from the reconstructed Čerenkov source, similar to the transmission process of photons in living organisms. In addition, the FSN further optimizes the reconstruction results of the ISN. To evaluate the performance of our proposed method, numerical simulation experiments and in vivo experiments were carried out. The results show that compared with the existing methods, this method can achieve superior performance in terms of location accuracy and shape recovery capability.
Funder
National Natural Science Foundation of China
Young Talent Support Program of Shaanxi Province University
China Postdoctoral Science Foundation
National Key Research and Development Program of China
Natural Science Foundation of Shaanxi Province
Young Talent Support Program of the Shaanxi Association for Science and Technology
Key Research and Development Program of Shaanxi Province
Major research and development project of Qinghai
Subject
General Physics and Astronomy
Cited by
1 articles.
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