Recognition for multiple sources of Bioluminescence tomography: a comparative study

Proceedings of SPIE(2018)

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Abstract
Bioluminescence tomography (BLT) can reconstruct internal bioluminescent source from the surface measurements. However, multiple sources resolving of BLT is always a challenge. In this work, a comparative study on hybrid clustering algorithm, synchronization-based clustering algorithm and iterative self-organizing data analysis technique algorithm for multiple sources recognition of BLT is conducted. Simulation experiments on two and three sources reconstruction are demonstrated the performances of these three algorithms. The results show that the iterative self-organizing data analysis technique is more suitable for the closer multiple-targets and the other two algorithms are suitable for distant targets. Moreover, iterative self-organizing data analysis technique has the least computing time.
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Key words
bioluminescence tomography,multiple-source resolving,hybrid clustering algorithm,synchronization-based clustering,iterative self-organizing data analysis technique
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