Level-set-based reconstruction algorithm for EIT lung images: first clinical results

被引：26

作者：

Rahmati, Peyman ^{[1
]}

Soleimani, Manuchehr ^{[2
]}

Pulletz, Sven ^{[3
]}

Frerichs, Inez ^{[3
]}

Adler, Andy ^{[1
]}

机构：

[1] Carleton Univ, Dept Syst & Comp Engn, Ottawa, ON K1S 5B6, Canada

[2] Univ Bath, Dept Elect & Elect Engn, Bath BA2 7AY, Avon, England

[3] Univ Med Ctr Schleswig Holstein, Dept Anaesthesiol & Intens Care Med, Kiel, Germany

来源：

PHYSIOLOGICAL MEASUREMENT | 2012年 / 33卷 / 05期

关键词：

electrical impedance tomography (EIT); inverse problems; finite element models; level set method; shape reconstruction; BRAIN;

D O I：

10.1088/0967-3334/33/5/739

中图分类号：

Q6 [生物物理学];

学科分类号：

071011 ;

摘要：

We show the first clinical results using the level-set-based reconstruction algorithm for electrical impedance tomography (EIT) data. The level-set-based reconstruction method (LSRM) allows the reconstruction of non-smooth interfaces between image regions, which are typically smoothed by traditional voxel-based reconstruction methods (VBRMs). We develop a time difference formulation of the LSRM for 2D images. The proposed reconstruction method is applied to reconstruct clinical EIT data of a slow flow inflation pressure-volume manoeuvre in lung-healthy and adult lung-injury patients. Images from the LSRM and the VBRM are compared. The results show comparable reconstructed images, but with an improved ability to reconstruct sharp conductivity changes in the distribution of lung ventilation using the LSRM.

引用

页码：739 / 750

页数：12

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