Detail publikace

Influence of Noise in Tissue Image Reconstruction

Originální název

Influence of Noise in Tissue Image Reconstruction

Anglický název

Influence of Noise in Tissue Image Reconstruction

Jazyk

en

Originální abstrakt

This paper describes the examination of new techniques for image reconstruction in electrical impedance tomography (EIT) in view of its influence to noise suppression. The examination was performed with respect to utilization in biomedical engineering. It is well known that while the forward problem is a well-posed task, the inverse problem is nonlinear and usually an ill-posed task. The presence of noise has huge impact on quality of image reconstruction. The recently described methods are based on deterministic or stochastic approach to solve 2D problems mainly. New technique, which uses the combination of well known methods for reconstruction EIT images - Tikhonov Regularization Method (TRM) and method used for image segmentation are presented. The presence of several noise magnitude levels is lead in and its influence on reconstructed image quality is observed. Numerical results of the image reconstruction procedures are presented and compared.

Anglický abstrakt

This paper describes the examination of new techniques for image reconstruction in electrical impedance tomography (EIT) in view of its influence to noise suppression. The examination was performed with respect to utilization in biomedical engineering. It is well known that while the forward problem is a well-posed task, the inverse problem is nonlinear and usually an ill-posed task. The presence of noise has huge impact on quality of image reconstruction. The recently described methods are based on deterministic or stochastic approach to solve 2D problems mainly. New technique, which uses the combination of well known methods for reconstruction EIT images - Tikhonov Regularization Method (TRM) and method used for image segmentation are presented. The presence of several noise magnitude levels is lead in and its influence on reconstructed image quality is observed. Numerical results of the image reconstruction procedures are presented and compared.

BibTex


@inproceedings{BUT29163,
  author="Tomáš {Kříž} and Ksenia {Kořínková}",
  title="Influence of Noise in Tissue Image Reconstruction",
  annote="This paper describes the examination of new techniques for image reconstruction in electrical impedance
tomography (EIT) in view of its influence to noise suppression. The examination was performed with respect to utilization in
biomedical engineering. It is well known that while the forward problem is a well-posed task, the inverse problem is
nonlinear and usually an ill-posed task. The presence of noise has huge impact on quality of image reconstruction. The
recently described methods are based on deterministic or stochastic approach to solve 2D problems mainly. New technique,
which uses the combination of well known methods for reconstruction EIT images - Tikhonov Regularization Method (TRM)
and method used for image segmentation are presented. The presence of several noise magnitude levels is lead in and its
influence on reconstructed image quality is observed. Numerical results of the image reconstruction procedures are presented
and compared.",
  booktitle="Elektro 2010 proceedings",
  chapter="29163",
  howpublished="print",
  year="2010",
  month="may",
  pages="53--56",
  type="conference paper"
}