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A quality-guided displacement tracking algorithm for ultrasonic elasticity imaging.

Chen L, Treece GM, Lindop JE, Gee AH, Prager RW - Med Image Anal (2008)

Bottom Line: This increases the accuracy and reduces the computational expense compared with exhaustive search.This paper introduces a novel displacement tracking algorithm, with a search strategy guided by a data quality indicator.Comparisons with existing methods show that the proposed algorithm is more robust when the displacement distribution is challenging.

View Article: PubMed Central - PubMed

Affiliation: Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK. lc420@eng.cam.ac.uk

ABSTRACT
Displacement estimation is a key step in the evaluation of tissue elasticity by quasistatic strain imaging. An efficient approach may incorporate a tracking strategy whereby each estimate is initially obtained from its neighbours' displacements and then refined through a localized search. This increases the accuracy and reduces the computational expense compared with exhaustive search. However, simple tracking strategies fail when the target displacement map exhibits complex structure. For example, there may be discontinuities and regions of indeterminate displacement caused by decorrelation between the pre- and post-deformation radio frequency (RF) echo signals. This paper introduces a novel displacement tracking algorithm, with a search strategy guided by a data quality indicator. Comparisons with existing methods show that the proposed algorithm is more robust when the displacement distribution is challenging.

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Related in: MedlinePlus

Same data as in Fig. 8a. Displacement obtained by the first (a) and second (b) passes of the multiple-seed algorithm. Seed propagation maps from the (c) first and (d) second passes. (For interpretation to colours in this figure, the reader is referred to the web version of this paper.)
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fig9: Same data as in Fig. 8a. Displacement obtained by the first (a) and second (b) passes of the multiple-seed algorithm. Seed propagation maps from the (c) first and (d) second passes. (For interpretation to colours in this figure, the reader is referred to the web version of this paper.)

Mentions: A multiple-seed approach is necessary for reliable tracking in such situations. Fig. 9a shows the displacement distribution retrieved by the first pass of the multiple-seed tracking algorithm. Accurate displacement estimates are obtained throughout the two well-correlated regions. The seed propagation map in Fig. 9c shows how spurious seeds inside the noisy region get a chance to grow towards the end of the tracking process, producing the bright patches in Fig. 9a.


A quality-guided displacement tracking algorithm for ultrasonic elasticity imaging.

Chen L, Treece GM, Lindop JE, Gee AH, Prager RW - Med Image Anal (2008)

Same data as in Fig. 8a. Displacement obtained by the first (a) and second (b) passes of the multiple-seed algorithm. Seed propagation maps from the (c) first and (d) second passes. (For interpretation to colours in this figure, the reader is referred to the web version of this paper.)
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2665204&req=5

fig9: Same data as in Fig. 8a. Displacement obtained by the first (a) and second (b) passes of the multiple-seed algorithm. Seed propagation maps from the (c) first and (d) second passes. (For interpretation to colours in this figure, the reader is referred to the web version of this paper.)
Mentions: A multiple-seed approach is necessary for reliable tracking in such situations. Fig. 9a shows the displacement distribution retrieved by the first pass of the multiple-seed tracking algorithm. Accurate displacement estimates are obtained throughout the two well-correlated regions. The seed propagation map in Fig. 9c shows how spurious seeds inside the noisy region get a chance to grow towards the end of the tracking process, producing the bright patches in Fig. 9a.

Bottom Line: This increases the accuracy and reduces the computational expense compared with exhaustive search.This paper introduces a novel displacement tracking algorithm, with a search strategy guided by a data quality indicator.Comparisons with existing methods show that the proposed algorithm is more robust when the displacement distribution is challenging.

View Article: PubMed Central - PubMed

Affiliation: Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK. lc420@eng.cam.ac.uk

ABSTRACT
Displacement estimation is a key step in the evaluation of tissue elasticity by quasistatic strain imaging. An efficient approach may incorporate a tracking strategy whereby each estimate is initially obtained from its neighbours' displacements and then refined through a localized search. This increases the accuracy and reduces the computational expense compared with exhaustive search. However, simple tracking strategies fail when the target displacement map exhibits complex structure. For example, there may be discontinuities and regions of indeterminate displacement caused by decorrelation between the pre- and post-deformation radio frequency (RF) echo signals. This paper introduces a novel displacement tracking algorithm, with a search strategy guided by a data quality indicator. Comparisons with existing methods show that the proposed algorithm is more robust when the displacement distribution is challenging.

Show MeSH
Related in: MedlinePlus