Curvelet denoising algorithm for medical ultrasound image based on adaptive threshold.
- Author:
Zhemin ZHUANG
;
Weike YAO
;
Jinyao YANG
;
FenLan LI
;
Ye YUAN
- Publication Type:Journal Article
- MeSH:
Algorithms;
Diagnostic Imaging;
Image Processing, Computer-Assisted;
Ultrasonics
- From:
Chinese Journal of Medical Instrumentation
2014;38(6):398-401
- CountryChina
- Language:Chinese
-
Abstract:
The traditional denoising algorithm for ultrasound images would lost a lot of details and weak edge information when suppressing speckle noise. A new denoising algorithm of adaptive threshold based on curvelet transform is proposed in this paper. The algorithm utilizes differences of coefficients' local variance between texture and smooth region in each layer of ultrasound image to define fuzzy regions and membership functions. In the end, using the adaptive threshold that determine by the membership function to denoise the ultrasound image. The experimental text shows that the algorithm can reduce the speckle noise effectively and retain the detail information of original image at the same time, thus it can greatly enhance the performance of B ultrasound instrument.
