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Fusion of Brushlet and Wavelet Denoising Methods for Nuclear Images

Elsa D. Angelini; Yinpeng Jin; Peter D. Esser; Ronald L. Van Heertum; Andrew F. Laine

Title:
Fusion of Brushlet and Wavelet Denoising Methods for Nuclear Images
Author(s):
Angelini, Elsa D.
Jin, Yinpeng
Esser, Peter D.
Van Heertum, Ronald L.
Laine, Andrew F.
Date:
Type:
Articles
Department:
Biomedical Engineering
Permanent URL:
Notes:
2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano: Arlington, VA, 15-18 April, 2004, vol. 2 (Piscataway, N.J.: IEEE, 2004), pp. 1187-1191.
Abstract:
This paper presents preliminary results on the fusion of denoised PET and SPECT data volumes from brushlet and wavelet thresholding methods. Texture-based brushlet denoising is well suited for enhancement of physiological information while wavelet-based denoising is better suited for enhancement of anatomical contours. A three-dimensional multiscale edge-based data fusion algorithm is applied to combine enhanced data from these two independent denoising methods. Preliminary results with qualitative evaluation of PET and SPECT data by an expert clinician showed great potential of this approach to combine enhancement of both anatomical and physiological signal information for improved image quality.
Subject(s):
Biomedical engineering
Publisher DOI:
http://dx.doi.org/10.1109/ISBI.2004.1398756
Item views:
281
Metadata:
text | xml

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