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| D Shape-based Fluorescence Molecular Tomography Through Hybrid Genetic Algorithm Based Optimization |
| WANG Dai-fa1,2, WANG Ling2, FAN Yu-bo2, LI De-yu2 |
1. State Key Laboratory of Software Development Environment, Beihang University, Beijing 100083, China；
2. School of Biological Science and Medical Engineering, Beihang University, Beijing 100083, China |
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Abstract Fluorescence molecular tomography (FMT) aims at tomographically resolving the fluorescent targets deeply inside small animal based on transmission boundary measurements. The image reconstruction of FMT is known to be highly ill-posed, due to the highly scattering nature of biological tissue. Hence, prior information is usually required for successful reconstruction. In this paper, a novel reconstruction method incorporating shape priors is proposed for 2D FMT. The fluorescent targets were assumed of round shape, which was practically appropriate for approximating various shapes inside diffusive medium. Compared to the traditional pixel based reconstruction, the number of unknowns was greatly reduced to a few control parameters of round shapes. A hybrid genetic algorithm was proposed to recover the shape parameters. The numerical experiments showed that the proposed method significantly improves the imaging accuracy, offering clearer target boundaries and better resolution. Comparison results also demonstrated that the hybridization of genetic algorithm and Newton-type search was pivotal and important for robustly finding the globally optimal shape parameters.
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Received: 15 July 2016
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Corresponding Authors:
WANG Dai-fa. E-mail: daifa.wang@buaa.edu.cn; deyuli@buaa.edu.cn
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