Detection of lines and boundaries in speckle images-application to medical ultrasound

Describes an approach to boundary detection in ultrasound speckle based on an image enhancement technique. The enhancement algorithm works by filtering the image with "sticks", short line segments which are varied in orientation to achieve the maximum projected value at each point. In this...

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Bibliographic Details
Published in:IEEE transactions on medical imaging 1999-02, Vol.18 (2), p.126-136
Main Authors: Czerwinski, R.N., Jones, D.L., O'Brien, W.D.
Format: Article
Language:English
Subjects:
Algorithms
Animals
Biological and medical sciences
Biomedical imaging
Color image processing
Detectors
Distribution functions
Edge detection
Filtering algorithms
Humans
Image edge detection
Image Enhancement
Image segmentation
Investigative techniques, diagnostic techniques (general aspects)
Medical sciences
Miscellaneous. Technology
Models, Theoretical
Shape
Speckle
Ultrasonic imaging
Ultrasonic investigative techniques
Ultrasonography - methods
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Description
Summary:Describes an approach to boundary detection in ultrasound speckle based on an image enhancement technique. The enhancement algorithm works by filtering the image with "sticks", short line segments which are varied in orientation to achieve the maximum projected value at each point. In this paper, we present three significant extensions to improve the performance of the basic method. First, we investigate the effect of varying the size and shape of the sticks. We show that these variations affect the performance of the algorithm in very fundamental ways, for example by making it more or less sensitive to thinner or more tightly curving boundaries. Second, we present a means of improving the performance of this technique by estimating the distribution function of the orientation of the line passing through each point. Finally, we show that images can be "stained" for easier visual interpretation by applying to each pixel a false color whose hue is related to the orientation of the most prominent line segment at that point. Examples are given to illustrate the performance of the different settings on a single image.
ISSN:0278-0062
1558-254X
DOI:10.1109/42.759114