Literature DB >> 10232669

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

R N Czerwinski1, D L Jones, W D O'Brien.   

Abstract

This paper 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. The statistical properties of this approach have been described in an earlier paper; in this work 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.

Mesh:

Year:  1999        PMID: 10232669     DOI: 10.1109/42.759114

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  17 in total

1.  An effective approach of lesion segmentation within the breast ultrasound image based on the cellular automata principle.

Authors:  Yan Liu; H D Cheng; Jianhua Huang; Yingtao Zhang; Xianglong Tang
Journal:  J Digit Imaging       Date:  2012-10       Impact factor: 4.056

2.  Hole filling with oriented sticks in ultrasound volume reconstruction.

Authors:  Thomas Vaughan; Andras Lasso; Tamas Ungi; Gabor Fichtinger
Journal:  J Med Imaging (Bellingham)       Date:  2015-08-12

3.  Automated 2D-3D registration of a radiograph and a cone beam CT using line-segment enhancement.

Authors:  Reshma Munbodh; David A Jaffray; Douglas J Moseley; Zhe Chen; Jonathan P S Knisely; Pascal Cathier; James S Duncan
Journal:  Med Phys       Date:  2006-05       Impact factor: 4.071

4.  Segmentation of elastographic images using a coarse-to-fine active contour model.

Authors:  Wu Liu; James A Zagzebski; Tomy Varghese; Charles R Dyer; Udomchai Techavipoo; Timothy J Hall
Journal:  Ultrasound Med Biol       Date:  2006-03       Impact factor: 2.998

5.  Enhancing ultrasound texture differences for developing an in vivo 'virtual histology' approach to bovine ovarian imaging.

Authors:  Mark G Eramian; Gregg P Adams; Roger A Pierson
Journal:  Reprod Fertil Dev       Date:  2007       Impact factor: 2.311

6.  Automated 2D-3D registration of portal images and CT data using line-segment enhancement.

Authors:  Reshma Munbodh; Zhe Chen; David A Jaffray; Douglas J Moseley; Jonathan P S Knisely; James S Duncan
Journal:  Med Phys       Date:  2008-10       Impact factor: 4.071

7.  An Artificial Immune System-Based Support Vector Machine Approach for Classifying Ultrasound Breast Tumor Images.

Authors:  Wen-Jie Wu; Shih-Wei Lin; Woo Kyung Moon
Journal:  J Digit Imaging       Date:  2015-10       Impact factor: 4.056

8.  Accurate model-based segmentation of gynecologic brachytherapy catheter collections in MRI-images.

Authors:  Andre Mastmeyer; Guillaume Pernelle; Ruibin Ma; Lauren Barber; Tina Kapur
Journal:  Med Image Anal       Date:  2017-07-18       Impact factor: 8.545

9.  Three Dimensional OCT in the Engineering of Tissue Constructs: A Potentially Powerful Tool for Assessing Optimal Scaffold Structure.

Authors:  K Zheng; M A Rupnick; B Liu; M E Brezinski
Journal:  Open Tissue Eng Regen Med J       Date:  2009

10.  Coronary angiography enhancement for visualization.

Authors:  Shengxian Tu; Gerhard Koning; Joan C Tuinenburg; Wouter Jukema; Su Zhang; Yazhu Chen; Johan H C Reiber
Journal:  Int J Cardiovasc Imaging       Date:  2009-07-26       Impact factor: 2.357

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