Robust strain estimation using adaptive dynamic grid interpolation model

Makoto Yamakawa; Shuhui Bu; Tsuyoshi Shiina

doi:10.1109/ULTSYM.2008.0498

Robust strain estimation using adaptive dynamic grid interpolation model

Makoto Yamakawa, Shuhui Bu, Tsuyoshi Shiina

Research output: Contribution to journal › Conference article › peer-review

1 Citation (Scopus)

Abstract

Tissue strain imaging is a new technology for imaging hardness information using ultrasound, and it is being used diagnosing breast cancer etc. However, the method currently used often induces errors in poor signal-to-noise ratio (SNR) such as low-echo areas. Therefore, this paper proposes a that can robustly estimate a strain distribution in poor areas. In order to use the adaptive dynamic grid (ADGI) model with a correlation coefficient in the method, errors in the poor SNR areas are corrected and high spatial resolution is maintained in the good SNR area.

Original language	English
Article number	4803533
Pages (from-to)	2021-2024
Number of pages	4
Journal	Proceedings - IEEE Ultrasonics Symposium
DOIs	https://doi.org/10.1109/ULTSYM.2008.0498
Publication status	Published - 2008
Externally published	Yes
Event	2008 IEEE International Ultrasonics Symposium, IUS 2008 - Beijing, China Duration: 2008 Nov 2 → 2008 Nov 5

Keywords

Adaptive dynamic grid interpolation model
Correlation coefficient
Displacement
Signal-to-noise ratio
Strain imaging

ASJC Scopus subject areas

Acoustics and Ultrasonics

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10.1109/ULTSYM.2008.0498

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title = "Robust strain estimation using adaptive dynamic grid interpolation model",

abstract = "Tissue strain imaging is a new technology for imaging hardness information using ultrasound, and it is being used diagnosing breast cancer etc. However, the method currently used often induces errors in poor signal-to-noise ratio (SNR) such as low-echo areas. Therefore, this paper proposes a that can robustly estimate a strain distribution in poor areas. In order to use the adaptive dynamic grid (ADGI) model with a correlation coefficient in the method, errors in the poor SNR areas are corrected and high spatial resolution is maintained in the good SNR area.",

keywords = "Adaptive dynamic grid interpolation model, Correlation coefficient, Displacement, Signal-to-noise ratio, Strain imaging",

author = "Makoto Yamakawa and Shuhui Bu and Tsuyoshi Shiina",

year = "2008",

doi = "10.1109/ULTSYM.2008.0498",

language = "English",

pages = "2021--2024",

journal = "Proceedings of the IEEE Ultrasonics Symposium",

issn = "1051-0117",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "2008 IEEE International Ultrasonics Symposium, IUS 2008 ; Conference date: 02-11-2008 Through 05-11-2008",

}

TY - JOUR

T1 - Robust strain estimation using adaptive dynamic grid interpolation model

AU - Yamakawa, Makoto

AU - Bu, Shuhui

AU - Shiina, Tsuyoshi

PY - 2008

Y1 - 2008

N2 - Tissue strain imaging is a new technology for imaging hardness information using ultrasound, and it is being used diagnosing breast cancer etc. However, the method currently used often induces errors in poor signal-to-noise ratio (SNR) such as low-echo areas. Therefore, this paper proposes a that can robustly estimate a strain distribution in poor areas. In order to use the adaptive dynamic grid (ADGI) model with a correlation coefficient in the method, errors in the poor SNR areas are corrected and high spatial resolution is maintained in the good SNR area.

AB - Tissue strain imaging is a new technology for imaging hardness information using ultrasound, and it is being used diagnosing breast cancer etc. However, the method currently used often induces errors in poor signal-to-noise ratio (SNR) such as low-echo areas. Therefore, this paper proposes a that can robustly estimate a strain distribution in poor areas. In order to use the adaptive dynamic grid (ADGI) model with a correlation coefficient in the method, errors in the poor SNR areas are corrected and high spatial resolution is maintained in the good SNR area.

KW - Adaptive dynamic grid interpolation model

KW - Correlation coefficient

KW - Displacement

KW - Signal-to-noise ratio

KW - Strain imaging

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UR - http://www.scopus.com/inward/citedby.url?scp=67649379413&partnerID=8YFLogxK

U2 - 10.1109/ULTSYM.2008.0498

DO - 10.1109/ULTSYM.2008.0498

M3 - Conference article

AN - SCOPUS:67649379413

SN - 1051-0117

SP - 2021

EP - 2024

JO - Proceedings of the IEEE Ultrasonics Symposium

JF - Proceedings of the IEEE Ultrasonics Symposium

M1 - 4803533

T2 - 2008 IEEE International Ultrasonics Symposium, IUS 2008

Y2 - 2 November 2008 through 5 November 2008

ER -

Robust strain estimation using adaptive dynamic grid interpolation model

Abstract

Keywords

ASJC Scopus subject areas

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