Abstract
Unmixing is often a necessary step to analyze 2D SPECT image sequence. However, factor analysis of dynamic sequences (FADS), the commonly used method for unmixing SPECT sequences, suffers from non-uniqueness issue. Optimization-based methods were developed to overcome this issue. These methods are effective but need improvement when the mixing is important or with very low SNR. In this paper, a new objective function using soft spatial prior knowledge is developed. Comparison with previous methods, efficiency and robustness to the choice of priors are illustrated with tests on synthetic dataset. Results on 2D SPECT sequences with high level of noise are also presented and compared.
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Filippi, M., Desvignes, M., Moisan, E., Ghezzi, C., Perret, P., Fagret, D. (2016). Factor Analysis of Dynamic Sequence with Spatial Prior for 2D Cardiac Spect Sequences Analysis. In: Blanc-Talon, J., Distante, C., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2016. Lecture Notes in Computer Science(), vol 10016. Springer, Cham. https://doi.org/10.1007/978-3-319-48680-2_21
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DOI: https://doi.org/10.1007/978-3-319-48680-2_21
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