Factor Analysis of Dynamic Sequence with Spatial Prior for 2D Cardiac Spect Sequences Analysis
| Autor: | Eric Moisan, Pascale Perret, Daniel Fagret, Marc Filippi, Michel Desvignes, Catherine Ghezzi |
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| Přispěvatelé: | GIPSA - Communication Information and Complex Systems (GIPSA-CICS), Département Images et Signal (GIPSA-DIS), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Radiopharmaceutiques biocliniques (LRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Filippi, Marc |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Spatial Priors
Computer science business.industry [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing 0211 other engineering and technologies [INFO.INFO-IM] Computer Science [cs]/Medical Imaging Source Separation Pattern recognition 02 engineering and technology 030218 nuclear medicine & medical imaging Penalized Least Squares 03 medical and health sciences 0302 clinical medicine [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Robustness (computer science) SPECT Prior probability Image sequence Source separation [INFO.INFO-IM]Computer Science [cs]/Medical Imaging Artificial intelligence business Factor Analysis 021101 geological & geomatics engineering |
| Zdroj: | Lecture Notes in Computer Science ACIVS 2016-International Conference on Advanced Concepts for Intelligent Vision Systems ACIVS 2016-International Conference on Advanced Concepts for Intelligent Vision Systems, Oct 2016, Lecce, Italy. pp.228-237, ⟨10.1007/978-3-319-48680-2_21⟩ Advanced Concepts for Intelligent Vision Systems ISBN: 9783319486796 ACIVS |
| DOI: | 10.1007/978-3-319-48680-2_21⟩ |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
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