DocumentCode :
3399713
Title :
Medical Image Denoising using X-lets
Author :
Parthiban, Latha ; Subramanian, Ramanathan
Author_Institution :
Dept. of Comput. Sci., Pondicherry Univ.
fYear :
2006
fDate :
Sept. 2006
Firstpage :
1
Lastpage :
6
Abstract :
Wavelets are proved to be well adapted for 1-D signal but can only capture limited directional information in 2D due to its poor orientation selectivity. Transforms like curvelets and contourlets have very high degree of directional specificity which is necessary for medical images. These transforms are based on certain anisotropic scaling principle which is quite different from the isotropic scaling of wavelets. Simulation test carried out on medical images like ultrasound images, magnetic resonance images and computerized tomography scan images, show that better denoising results were obtained by curvelets and contourlets, than with wavelets, in terms of mean square error, signal to noise ratio and visual evaluation
Keywords :
biomedical MRI; biomedical ultrasonics; computerised tomography; curvelet transforms; diagnostic radiography; image denoising; mean square error methods; medical image processing; anisotropic scaling; computerized tomography scan images; contourlets denoising techniques; curvelet denoising techniques; magnetic resonance images; mean square error; medical image denoising; signal-to-noise ratio; ultrasound images; visual evaluation; Anisotropic magnetoresistance; Biomedical imaging; Computational modeling; Computer simulation; Image denoising; Magnetic resonance; Medical simulation; Medical tests; Ultrasonic imaging; Wavelet transforms; Computerized Tomography; Contourlets; Curvelets; Magnetic Resonance Imaging; Mean Square Error; Peak Signal to Noise Ratio; Wavelet Transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
India Conference, 2006 Annual IEEE
Conference_Location :
New Delhi
Print_ISBN :
1-4244-0369-3
Electronic_ISBN :
1-4244-0370-7
Type :
conf
DOI :
10.1109/INDCON.2006.302763
Filename :
4086234
Link To Document :
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