DocumentCode :
140262
Title :
Speckle reduction by phase-based weighted least squares
Author :
Lei Zhu ; Weiming Wang ; Jing Qin ; Pheng-Ann Heng
Author_Institution :
Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, China
fYear :
2014
fDate :
26-30 Aug. 2014
Firstpage :
3909
Lastpage :
3912
Abstract :
Although ultrasonography has been widely used in clinical applications, the doctor suffers great difficulties in diagnosis due to the artifacts of ultrasound images, especially the speckle noise. This paper proposes a novel framework for speckle reduction by using a phase-based weighted least squares optimization. The proposed approach can effectively smooth out speckle noise while preserving the features in the image, e.g., edges with different contrasts. To this end, we first employ a local phase-based measure, which is theoretically intensity-invariant, to extract the edge map from the input image. The edge map is then incorporated into the weighted least squares framework to supervise the optimization during despeckling, so that low contrast edges can be retained while the noise has been greatly removed. Experimental results in synthetic and clinical ultrasound images demonstrate that our approach performs better than state-of-the-art methods.
Keywords :
biomedical ultrasonics; edge detection; feature extraction; image denoising; least mean squares methods; medical image processing; optimisation; speckle; edge map extraction; feature extraction; local phase-based measure; phase-based weighted least squares optimization; speckle noise reduction; ultrasonography; ultrasound images; Image edge detection; Noise; Phase measurement; Smoothing methods; Speckle; Ultrasonic imaging; Ultrasonic variables measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
ISSN :
1557-170X
Type :
conf
DOI :
10.1109/EMBC.2014.6944478
Filename :
6944478
Link To Document :
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