Detail publikace

Choice of suitable wavelets for MR image processing

Originální název

Choice of suitable wavelets for MR image processing

Anglický název

Choice of suitable wavelets for MR image processing

Jazyk

en

Originální abstrakt

Magnetic nuclear resonance is used in particular as a diagnostic imaging method. Images of selected parts of organs must be of sufficient quality for doctors to be able to not miss any details and to make reliable diagnoses. The detected images are often of low contrast and resolution. They are mainly subjected to noise, whose level depends, among other things, on the level of the signal being detected, local proton density, voxel size, bandwidth, system design, quality of RF coil, and detection parameters [1], [2], [3]. Noise is in the same frequency band as the image spectral components that carry the details. Suppressing noise without knowing its properties must be a compromise between the desired smoothing and improvement of signal to-noise-ratio (SNR) on the one hand and the loss of details on the other hand. If the filtering method is applied in order to remove noise from MR images, a correct choice of individual filtering parameters is important. In the paper, the selection is described of wavelets suitable for improving the quality of MR images of temporomandibular joint [4] and their evaluation according to three criteria: increased SNR, steepness of the change in signal intensity in the image, and the change in contrast.

Anglický abstrakt

Magnetic nuclear resonance is used in particular as a diagnostic imaging method. Images of selected parts of organs must be of sufficient quality for doctors to be able to not miss any details and to make reliable diagnoses. The detected images are often of low contrast and resolution. They are mainly subjected to noise, whose level depends, among other things, on the level of the signal being detected, local proton density, voxel size, bandwidth, system design, quality of RF coil, and detection parameters [1], [2], [3]. Noise is in the same frequency band as the image spectral components that carry the details. Suppressing noise without knowing its properties must be a compromise between the desired smoothing and improvement of signal to-noise-ratio (SNR) on the one hand and the loss of details on the other hand. If the filtering method is applied in order to remove noise from MR images, a correct choice of individual filtering parameters is important. In the paper, the selection is described of wavelets suitable for improving the quality of MR images of temporomandibular joint [4] and their evaluation according to three criteria: increased SNR, steepness of the change in signal intensity in the image, and the change in contrast.

BibTex


@inproceedings{BUT30069,
  author="Karel {Bartušek} and Eva {Gescheidtová}",
  title="Choice of suitable wavelets for MR image processing",
  annote="Magnetic nuclear resonance is used in particular as a diagnostic imaging method. Images of selected parts of organs must be of sufficient quality for doctors to be able to not miss any details and to make reliable diagnoses. The detected images are often of low contrast and resolution. They are mainly subjected to noise, whose level depends, among other things, on the level of the signal being detected, local proton density, voxel size, bandwidth, system design, quality of RF coil, and detection parameters [1], [2], [3]. Noise is in the same frequency band as the image spectral components that carry the details. Suppressing noise without knowing its properties must be a compromise between the desired smoothing and improvement of signal to-noise-ratio (SNR) on the one hand and the loss of details on the other hand. If the filtering method is applied in order to remove noise from MR images, a correct choice of individual filtering parameters is important.
In the paper, the selection is described of wavelets suitable for improving the quality of MR images of temporomandibular joint [4] and their evaluation according to three criteria: increased SNR, steepness of the change in signal intensity in the image, and the change in contrast.",
  address="Tne Electromagnetic Academy",
  booktitle="PIERS 2010 Xian",
  chapter="30069",
  howpublished="print",
  institution="Tne Electromagnetic Academy",
  year="2010",
  month="march",
  pages="1565--1568",
  publisher="Tne Electromagnetic Academy",
  type="conference paper"
}