电阻抗断层成像
体积热力学
断层摄影术
计算机科学
参数统计
噪音(视频)
电阻抗
算法
数学
人工智能
工程类
医学
图像(数学)
统计
放射科
物理
电气工程
量子力学
作者
Thomas Schlebusch,Steffen Nienke,Steffen Leonhardt,Marian Walter
出处
期刊:Physiological Measurement
[IOP Publishing]
日期:2014-08-20
卷期号:35 (9): 1813-1823
被引量:45
标识
DOI:10.1088/0967-3334/35/9/1813
摘要
Non-invasive estimation of bladder volume is required to progress from scheduled voiding to a demand-driven emptying scheme for patients with impaired bladder volume sensation. Electrical impedance tomography (EIT) is a promising candidate for the non-invasive monitoring of bladder volume. This article focuses on four estimation algorithms used to map recorded EIT data to a volume estimate. Two different approaches are presented: the tomographic algorithms (one based on global impedance, the other on equivalent circular diameter) rely on the reconstruction of a tomographic image and then extract a volume estimate, whereas the parametric algorithms (one based on neural networks, the other on the singular value difference method) directly map the raw data to a volume estimate. The four algorithms presented here are evaluated for volume estimation error, noise tolerance and suppression of varying urine conductivity based on finite element simulation data.
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