Wavelet-based texture analysis in multiple sclerosis using quantitative MRI
Zagar B. (Hrsg). Proceedings of the Seventh IASTED International Conference on Signal Processing, Pattern Recognition and Applications : February 17 - 19, 2010, Innsbruck, Austria 4060 IV, 385 S. Anaheim, Calif. [u.a.]: Acta-Press 2010 S. 304 - 309
Erscheinungsjahr: 2010
ISBN/ISSN: 978-0-88986-822-9
Publikationstyp: Buchbeitrag (Konferenzbeitrag)
Sprache: Englisch
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Inhaltszusammenfassung
This paper deals with an application of the two dimensional wavelet transform to MRI data. The main goal is to employ the DWT for finding peaks and irregular features in the white matter of brain scans of multiple sclerosis patients. After masking the region of interest a one level wavelet transform already yields some interesting hints for the distinction between healthy and diseased probands. The comparison of histograms of wavelet coefficients between both groups obviously shows two differ...This paper deals with an application of the two dimensional wavelet transform to MRI data. The main goal is to employ the DWT for finding peaks and irregular features in the white matter of brain scans of multiple sclerosis patients. After masking the region of interest a one level wavelet transform already yields some interesting hints for the distinction between healthy and diseased probands. The comparison of histograms of wavelet coefficients between both groups obviously shows two different distributions. A hypothesis about the different shapes of these distributions might give interesting additional information with respect to classifying the MRI data» weiterlesen» einklappen
Klassifikation
DFG Fachgebiet:
Mathematik
DDC Sachgruppe:
Mathematik
