Validation of an inverse parameter estimation algorithm for determining material properties of passive myocardium

Michael J. Moulton; Julius M. Guccione; Ruth J. Okamoto; Michael K. Pasque

Validation of an inverse parameter estimation algorithm for determining material properties of passive myocardium

Michael J. Moulton
, Julius M. Guccione
, Ruth J. Okamoto
, Michael K. Pasque

Research output: Contribution to conference › Paper › peer-review

Abstract

A material identification algorithm is described for determining in vivo material properties of diastolic myocardium. A nonlinear optimization algorithm is employed to solve a least squares objective function. The objective function relates the least squares difference of model-predicted strains obtained from a finite element (FE) solution to measured strains obtained in the in vivo case from magnetic resonance imaging radiofrequency tissue-tagging. The algorithm is validated using a three-dimensional, nonlinear, anisotropic FE model by examining the effects of noise in the measured data on a priori given parameter solutions.

Original language	English
Pages	33-34
Number of pages	2
State	Published - 1995
Event	Proceedings of the 1995 ASME International Mechanical Congress and Exposition - San Francisco, CA, USA Duration: Nov 12 1995 → Nov 17 1995

Conference

Conference	Proceedings of the 1995 ASME International Mechanical Congress and Exposition
City	San Francisco, CA, USA
Period	11/12/95 → 11/17/95

Cite this

@conference{a525cd874cf548f2a44a3fb673a092de,

title = "Validation of an inverse parameter estimation algorithm for determining material properties of passive myocardium",

abstract = "A material identification algorithm is described for determining in vivo material properties of diastolic myocardium. A nonlinear optimization algorithm is employed to solve a least squares objective function. The objective function relates the least squares difference of model-predicted strains obtained from a finite element (FE) solution to measured strains obtained in the in vivo case from magnetic resonance imaging radiofrequency tissue-tagging. The algorithm is validated using a three-dimensional, nonlinear, anisotropic FE model by examining the effects of noise in the measured data on a priori given parameter solutions.",

author = "Moulton, \{Michael J.\} and Guccione, \{Julius M.\} and Okamoto, \{Ruth J.\} and Pasque, \{Michael K.\}",

year = "1995",

language = "English",

pages = "33--34",

note = "Proceedings of the 1995 ASME International Mechanical Congress and Exposition ; Conference date: 12-11-1995 Through 17-11-1995",

}

Validation of an inverse parameter estimation algorithm for determining material properties of passive myocardium. / Moulton, Michael J.; Guccione, Julius M.; Okamoto, Ruth J. et al.
1995. 33-34 Paper presented at Proceedings of the 1995 ASME International Mechanical Congress and Exposition, San Francisco, CA, USA.

Research output: Contribution to conference › Paper › peer-review

TY - CONF

T1 - Validation of an inverse parameter estimation algorithm for determining material properties of passive myocardium

AU - Moulton, Michael J.

AU - Guccione, Julius M.

AU - Okamoto, Ruth J.

AU - Pasque, Michael K.

PY - 1995

Y1 - 1995

N2 - A material identification algorithm is described for determining in vivo material properties of diastolic myocardium. A nonlinear optimization algorithm is employed to solve a least squares objective function. The objective function relates the least squares difference of model-predicted strains obtained from a finite element (FE) solution to measured strains obtained in the in vivo case from magnetic resonance imaging radiofrequency tissue-tagging. The algorithm is validated using a three-dimensional, nonlinear, anisotropic FE model by examining the effects of noise in the measured data on a priori given parameter solutions.

AB - A material identification algorithm is described for determining in vivo material properties of diastolic myocardium. A nonlinear optimization algorithm is employed to solve a least squares objective function. The objective function relates the least squares difference of model-predicted strains obtained from a finite element (FE) solution to measured strains obtained in the in vivo case from magnetic resonance imaging radiofrequency tissue-tagging. The algorithm is validated using a three-dimensional, nonlinear, anisotropic FE model by examining the effects of noise in the measured data on a priori given parameter solutions.

UR - https://www.scopus.com/pages/publications/0029425455

M3 - Paper

AN - SCOPUS:0029425455

SP - 33

EP - 34

T2 - Proceedings of the 1995 ASME International Mechanical Congress and Exposition

Y2 - 12 November 1995 through 17 November 1995

ER -

Validation of an inverse parameter estimation algorithm for determining material properties of passive myocardium

Abstract

Conference

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