Detail publikace

Criteria for wavelet selection in MR image filtering

Originální název

Criteria for wavelet selection in MR image filtering

Anglický název

Criteria for wavelet selection in MR image filtering

Jazyk

en

Originální abstrakt

Magnetic resonance is made use of in particular as a diagnostic imaging method. To be able to reliably establish a diagnosis, the doctors must have at their disposal images of selected parts of human organs that are of sufficient quality, with no details missing. The detected images are frequently of very low contrast and resolution. Similar to MR signals, the images are degraded by noise, the level of which depends, among other things, on the level of the signal being detected, local proton density, voxel size, bandwidth, system design, quality of the RF coil, and the detection parameters. The introduction of wavelet transform provided an efficient tool for processing not only MR signals but also MR images. For a successful processing of images it is important to select from the many currently used types of wavelet. An inappropriate choice of the wavelet can lead to the loss of important information contained in the image or, on the contrary, filtering can be less efficient. In the paper the selection criteria are described and their importance in the selection of wavelets suitable for MR image processing is evaluated.

Anglický abstrakt

Magnetic resonance is made use of in particular as a diagnostic imaging method. To be able to reliably establish a diagnosis, the doctors must have at their disposal images of selected parts of human organs that are of sufficient quality, with no details missing. The detected images are frequently of very low contrast and resolution. Similar to MR signals, the images are degraded by noise, the level of which depends, among other things, on the level of the signal being detected, local proton density, voxel size, bandwidth, system design, quality of the RF coil, and the detection parameters. The introduction of wavelet transform provided an efficient tool for processing not only MR signals but also MR images. For a successful processing of images it is important to select from the many currently used types of wavelet. An inappropriate choice of the wavelet can lead to the loss of important information contained in the image or, on the contrary, filtering can be less efficient. In the paper the selection criteria are described and their importance in the selection of wavelets suitable for MR image processing is evaluated.

BibTex


@inproceedings{BUT30068,
  author="Eva {Gescheidtová} and Karel {Bartušek}",
  title="Criteria for wavelet selection in MR image filtering",
  annote="Magnetic resonance is made use of in particular as a diagnostic imaging method. To be able to reliably establish a diagnosis, the doctors must have at their disposal images of selected parts of human organs that are of sufficient quality, with no details missing. The detected images are frequently of very low contrast and resolution. Similar to MR signals, the images are degraded by noise, the level of which depends, among other things, on the level of the signal being detected, local proton density, voxel size, bandwidth, system design, quality of the RF coil, and the detection parameters. The introduction of wavelet transform provided an efficient tool for processing not only MR signals but also MR images. For a successful processing of images it is important to select from the many currently used types of wavelet. An inappropriate choice of the wavelet can lead to the loss of important information contained in the image or, on the contrary, filtering can be less efficient.
In the paper the selection criteria are described and their importance in the selection of wavelets suitable for MR image processing is evaluated.",
  address="The Electromagnetic Academy",
  booktitle="PIERS 2010 Xian",
  chapter="30068",
  howpublished="electronic, physical medium",
  institution="The Electromagnetic Academy",
  year="2010",
  month="march",
  pages="1569--1572",
  publisher="The Electromagnetic Academy",
  type="conference paper"
}