Estimation of Volumetric Myocardial Apparent Conductivity From Endocardial Electro-Anatomical Mapping

被引：3

作者：

Chinchapatnam, Phani ^{[1
]}

Rhode, Kawal S. ^{[2
]}

Ginks, Matthew ^{[2
]}

Mansi, Tommaso ^{[3
]}

Peyrat, Jean-Marc ^{[3
]}

Lambiase, Pier ^{[5
]}

Rinaldi, C. Aldo ^{[4
]}

Razavi, Reza ^{[2
]}

Arridge, Simon ^{[1
]}

Sermesant, Maxime ^{[3
,6
]}

机构：

[1] UCL, Ctr Med Image Comp, Gower St, London WC1E 6BT, England

[2] St Thomas Hosp, Coll London, Inter Dispciplinary Med Image Grp, Div Imaging Sci, London SE1 7EH, England

[3] INRIA, Sophia Antipolis, France

[4] St Thomas Hosp, Dept Cardiol, London SE1 7EH, England

[5] Univ Coll London Hosp, Heart Hosp, London, England

[6] St Thomas Hosp, Kings Coll London, Div Imaging Sci, London SE1 7EH, England

来源：

2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20 | 2009年

基金：

英国工程与自然科学研究理事会;

关键词：

COMPUTATIONAL PHYSIOLOGY; PROPAGATION; MODELS;

D O I：

10.1109/IEMBS.2009.5334441

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Estimating patient-specific electrical tissue parameters is of considerable benefit towards personalisation of cardiac biophysical models. In this paper, an adaptive inverse parameter estimation algorithm is proposed to estimate the myocardial apparent conductivity from endocardial electrical potential measurements. The forward electrophysiology problem is posed as an Eikonal model and is solved using an anisotropic fast marching method. The conductivity estimation algorithm is validated on patient data obtained using hybrid X-ray/magnetic resonance imaging. Future directions towards improving such estimation procedures are also indicated.

引用

页码：2907 / 2910

页数：4

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