DocumentCode
790514
Title
Mode filtering to reduce ultrasound speckle for feature extraction
Author
Evans, A.N. ; Nixon, M.S.
Author_Institution
Dept. of Electron. & Comput. Sci., Southampton Univ., UK
Volume
142
Issue
2
fYear
1995
fDate
4/1/1995 12:00:00 AM
Firstpage
87
Lastpage
94
Abstract
The authors investigate the use of filtering techniques to reduce speckle in ultrasound images, to improve their suitability for later feature extraction. The maximum likelihood estimator for a speckle corrupted image is shown to correspond to the statistical mode but this is difficult to determine for small populations, such as those contained by a filter mask. The truncated median filter approximates the mode by using the order of known image statistics and provides a fully automated image processing technique for speckle filtering. The filter´s performance is established using a new quantitative evaluation scheme that closely considers the effect of filtering on edges, a key factor when applying features extraction in automated image interpretation. Application to in vivo and phantom test images shows that the truncated median filter provides clear images with strong edges, of quality exceeding that of other techniques. These benefits are confirmed by the application of feature extraction in arterial wall labelling
Keywords
biomedical ultrasonics; feature extraction; filtering theory; maximum likelihood estimation; median filters; medical image processing; speckle; arterial wall labelling; automated image interpretation; automated image processing; feature extraction; filter mask; filter performance; image quality; image statistics; in vivo test images; maximum likelihood estimator; mode filtering; phantom test images; speckle corrupted image; speckle filtering; statistical mode; truncated median filter; ultrasound images; ultrasound speckle reduction;
fLanguage
English
Journal_Title
Vision, Image and Signal Processing, IEE Proceedings -
Publisher
iet
ISSN
1350-245X
Type
jour
DOI
10.1049/ip-vis:19951800
Filename
388400
Link To Document