Statistical Characterization of Portal Images and Noise from Portal Imaging Systems.

In this paper, we consider the statistical characteristics of the so-called portal images, which are acquired prior to the radiotherapy treatment, as well as the noise that present the portal imaging systems, in order to analyze whether the well-known noise and image features in other image modaliti...

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Publicado en:Journal of Digital Imaging Vol. 26; no. 3; pp. 457 - 466
Autores principales: González-López, Antonio, Morales-Sánchez, Juan, Verdú-Monedero, Rafael, Larrey-Ruiz, Jorge
Formato: diagnostic images tables/charts Journal Article
Publicado: Springer Nature Jun2013
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
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        atl: Statistical Characterization of Portal Images and Noise from Portal Imaging Systems.
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          González-López, Antonio
          Morales-Sánchez, Juan
          Verdú-Monedero, Rafael
          Larrey-Ruiz, Jorge
        affil: Servicio de Radiofísica y Protección Radiológica, Hospital Universitario Virgen de la Arrixaca, Ctra. Madrid-Cartagena 30120 El Palmar (Murcia) Spain
      sug:
        subj:
          Radiotherapy
          Radiotherapy, Computer-Assisted
          Simulations
          Artifacts
          Statistics
          Radiographic Magnification
      ab: In this paper, we consider the statistical characteristics of the so-called portal images, which are acquired prior to the radiotherapy treatment, as well as the noise that present the portal imaging systems, in order to analyze whether the well-known noise and image features in other image modalities, such as natural image, can be found in the portal imaging modality. The study is carried out in the spatial image domain, in the Fourier domain, and finally in the wavelet domain. The probability density of the noise in the spatial image domain, the power spectral densities of the image and noise, and the marginal, joint, and conditional statistical distributions of the wavelet coefficients are estimated. Moreover, the statistical dependencies between noise and signal are investigated. The obtained results are compared with practical and useful references, like the characteristics of the natural image and the white noise. Finally, we discuss the implication of the results obtained in several noise reduction methods that operate in the wavelet domain.
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      doctype:
        diagnostic images
        tables/charts
        Journal Article
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    language: English
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