Compartment model-based nonlinear unmixing for kinetic analysis of dynamic PET images Article Swipe
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· 2020
· Open Access
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· DOI: https://doi.org/10.48550/arxiv.2011.10097
When no arterial input function is available, quantification of dynamic PET images requires a previous step devoted to the extraction of a reference time-activity curve (TAC). Factor analysis is often applied for this purpose. This paper introduces a novel approach that conducts a new kind of nonlinear factor analysis relying on a compartment model, and computes the kinetic parameters of specific binding tissues jointly. To this end, it capitalizes on data-driven parametric imaging methods to provide a physical description of the underlying PET data, directly relating the specific binding with the kinetics of the non-specific binding in the corresponding tissues. This characterization is introduced into the factor analysis formulation to yield a novel nonlinear unmixing model designed for PET image analysis. This model also explicitly introduces global kinetic parameters that allow for a direct estimation of the binding potential with respect to the free fractions in each non-specific binding tissue. The performance of the method is evaluated on synthetic and real data to demonstrate its potential interest.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.48550/arxiv.2011.10097
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4309520819Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2011.10097Digital Object Identifier
- Title
-
Compartment model-based nonlinear unmixing for kinetic analysis of dynamic PET imagesWork title
- Type
-
preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
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2020-11-19Full publication date if available
- Authors
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Yanna Cruz Cavalcanti, Thomas Oberlin, Vinicius Ferraris, Nicolas Dobigeon, Maria Ribeiro, Clovis TauberList of authors in order
- Landing page
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https://doi.org/10.48550/arxiv.2011.10097Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://doi.org/10.48550/arxiv.2011.10097Direct OA link when available
- Concepts
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Nonlinear system, Biological system, Computer science, Parametric statistics, Compartment (ship), Function (biology), Parametric model, Artificial intelligence, Algorithm, Mathematics, Physics, Statistics, Evolutionary biology, Geology, Oceanography, Biology, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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