A statistical detection of an anomaly from a few noisy tomographic projections (Q2502642)
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| Language | Label | Description | Also known as |
|---|---|---|---|
| English | A statistical detection of an anomaly from a few noisy tomographic projections |
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A statistical detection of an anomaly from a few noisy tomographic projections (English)
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13 September 2006
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Summary: The problem of detecting an anomaly/target from a very limited number of noisy tomographic projections is addressed from the statistical point of view. The imaged object is composed of an environment, considered as a nuisance parameter, with a possibly hidden anomaly/target. The GLR test is used to solve the problem. When the projection linearly depends on the nuisance parameters, the GLR test coincides with an optimal statistical invariant test.
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statistical hypotheses testing
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(non)linear parametric model
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nuisance parameter
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invariant tests
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missing observations
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computerized tomography
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numerical examples
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reconstruction from projections
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nonlinear regression
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Radon transform
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