Bioluminescence tomography via a shape optimization method based on a complex-valued model

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Hauptverfasser: Wu, Qianqian, Gong, Rongfang, Gong, Wei, Zhang, Ziyi, Zhu, Shengfeng
Format: Preprint
Veröffentlicht: 2025
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author Wu, Qianqian
Gong, Rongfang
Gong, Wei
Zhang, Ziyi
Zhu, Shengfeng
author_facet Wu, Qianqian
Gong, Rongfang
Gong, Wei
Zhang, Ziyi
Zhu, Shengfeng
contents In this study, we investigate the inverse source problem arising in bioluminescence tomography, the objective of which is to reconstruct both the support and the intensity of an internal light source from boundary measurements governed by an elliptic model. A shape optimization framework is developed in which the source intensity and its support are decoupled through first-order optimality conditions. To enhance the stability of the reconstruction, we incorporate a parameter-dependent coupled complex boundary method together with perimeter and volume regularizations. Source support is represented by a level set function, allowing the algorithm to naturally accommodate topological changes and recover multiple, closely spaced, or nested source regions. Theoretical justifications for the proposed formulation and regularization strategy are established, and extensive numerical experiments are performed to assess the reconstruction accuracy for both noise-free and noisy data. The results demonstrate that our method achieves robust and accurate recovery of source geometry and intensity, and exhibits clear advantages over existing approaches.
format Preprint
id arxiv_https___arxiv_org_abs_2509_09533
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Bioluminescence tomography via a shape optimization method based on a complex-valued model
Wu, Qianqian
Gong, Rongfang
Gong, Wei
Zhang, Ziyi
Zhu, Shengfeng
Numerical Analysis
Optimization and Control
In this study, we investigate the inverse source problem arising in bioluminescence tomography, the objective of which is to reconstruct both the support and the intensity of an internal light source from boundary measurements governed by an elliptic model. A shape optimization framework is developed in which the source intensity and its support are decoupled through first-order optimality conditions. To enhance the stability of the reconstruction, we incorporate a parameter-dependent coupled complex boundary method together with perimeter and volume regularizations. Source support is represented by a level set function, allowing the algorithm to naturally accommodate topological changes and recover multiple, closely spaced, or nested source regions. Theoretical justifications for the proposed formulation and regularization strategy are established, and extensive numerical experiments are performed to assess the reconstruction accuracy for both noise-free and noisy data. The results demonstrate that our method achieves robust and accurate recovery of source geometry and intensity, and exhibits clear advantages over existing approaches.
title Bioluminescence tomography via a shape optimization method based on a complex-valued model
topic Numerical Analysis
Optimization and Control
url https://arxiv.org/abs/2509.09533