Iborra, A.; Rodríguez-Álvarez, MJ.; Soriano, A.; Sánchez, F.; Bellido, P.; Conde, P.; Crespo, E.... (2013). Effect of noise in CT image reconstruction using QR- Decomposition algorithm. IEEE. 5-9. http://hdl.handle.net/10251/167122
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/167122
Título:
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Effect of noise in CT image reconstruction using QR- Decomposition algorithm
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Autor:
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Iborra, A.
Rodríguez-Álvarez, M. J.
Soriano, A.
Sánchez, F.
Bellido, P.
Conde, P.
Crespo, E.
González Martínez, Antonio Javier
Martos, F.
Moliner, L.
Rigla, J. P.
Seimetz, Michael
Vidal San Sebastian, Luis Fernando
Benlloch Baviera, Jose María
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Entidad UPV:
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Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada
Universitat Politècnica de València. Instituto de Instrumentación para Imagen Molecular - Institut d'Instrumentació per a Imatge Molecular
Universitat Politècnica de València. Instituto Universitario Mixto de Biología Molecular y Celular de Plantas - Institut Universitari Mixt de Biologia Molecular i Cel·lular de Plantes
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Fecha difusión:
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Resumen:
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[EN] The QR-Decomposition algorithm for CT 3D image
reconstruction uses a linear system of equations to model the
CT system response. Linear systems have a condition number
that can be used to estimate the image noise. ...[+]
[EN] The QR-Decomposition algorithm for CT 3D image
reconstruction uses a linear system of equations to model the
CT system response. Linear systems have a condition number
that can be used to estimate the image noise. In this work the
number of projections and the number of pixels in the detector
have been studied to characterize the CT and the linear system
of equations. The condition number of the system is estimated for
the previous parameters used to generate the CT model with the
aim of characterizing how these parameters affect the condition
number and therefore bound the image noise level. It is shown
that the condition number mainly depends on the size of pixels
of the detector rather than the number of projections and this
algorithm can be applied to low dose CT 3D image reconstruction
without compromising image quality
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Palabras clave:
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Medical imaging
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Image reconstruction
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QR decomposition
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Image noise
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Derechos de uso:
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Reserva de todos los derechos
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ISBN:
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978-1-4799-0534-8
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Fuente:
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2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (2013 NSS/MIC).
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Editorial:
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IEEE
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Versión del editor:
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https://ieeexplore.ieee.org/xpl/conhome/6819718/proceeding
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Título del congreso:
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IEEE Nuclear Science Symposium and Medical Imaging Conference, and Room-Temperature Semiconductor X-Ray and Gamma-Ray Detectors Workshop (2013 IEEE NSS/MIC/RTSD)
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Lugar del congreso:
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Seoul, Korea
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Fecha congreso:
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Octubre 27-Noviembre 02,2013
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Código del Proyecto:
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info:eu-repo/grantAgreement/GVA//PROMETEOII%2F2013%2F010/
info:eu-repo/grantAgreement/GVA//ISIC 2011%2F013/
info:eu-repo/grantAgreement/MICINN//FIS2010-21216-C02-01/ES/DESARROLLO DEL DETECTOR PET%2FRM PARA DIAGNOSTICO DE ENFERMEDADES NEURODEGENERATIVAS./
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Agradecimientos:
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This work was supported by the Spanish Plan Nacional de Investigacion Científica, Desarrollo e Innovación Tecnológica (I+D+I) under Grant No. FIS2010-21216-CO2-01 and Valencian Local Government under Grants PROMETEOII/2013/010 ...[+]
This work was supported by the Spanish Plan Nacional de Investigacion Científica, Desarrollo e Innovación Tecnológica (I+D+I) under Grant No. FIS2010-21216-CO2-01 and Valencian Local Government under Grants PROMETEOII/2013/010 and ISIC 2011/013
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Tipo:
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Comunicación en congreso
Capítulo de libro
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