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Cited by 438

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

A novel method for angle independent ultrasonic imaging of blood flow and tissue motion

Bohs, L.N., Trahey, G.E.·1991·IEEE Transactions on Biomedical Engineering

Abstract

Tracking the speckle patterns produced by moving targets has been shown effective for angle independent imaging of blood flow and tissue motion. While speckle tracking overcomes major limitations of Doppler-based flow imaging, the computational complexity of commonly used cross correlation algorithms currently limits it to off-line studies. A much simpler algorithm for angle independent motion imaging is described in this paper. This method requires only one absolute difference operation per pixel, compared to eight operations for normalized cross correlation. Quantitative studies using speckle-generating targets translated by fixed amounts both axially and laterally indicate that the technique tracks moving speckle as accurately as correlation. Color flow images generated from clinical blood and liver data highlight the success of the technique for tracking both large and small motions in two dimensions. The algorithm's suitability for implementation in digital hardware makes possible the development of clinical instruments for angle independent ultrasonic imaging of blood flow and tissue motion in real time.

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Metadata

Authors
Bohs, L. N., & Trahey, G. E.
Venue
IEEE Transactions on Biomedical Engineering
Published
1991-03
Volume
38
Issue
3
Pages
280-286
ISSN
0018-9294 (ISSN-L)
OpenAlex
W2100194764
Cited by
438
References
7
FWCI
11.24
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A novel method for angle independent ultrasonic imaging of blood flow and tissue motion. https://app.cochat.ai/papers/10.1109/10.133210
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Bohs, L. N., & Trahey, G. E. (1991). A novel method for angle independent ultrasonic imaging of blood flow and tissue motion. IEEE Transactions on Biomedical Engineering. https://doi.org/10.1109/10.133210

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.