Paper Info
Title
Inverse modeling for heat conduction problem in human abdominal phantom.
Abstract
Noninvasive methods for deep body temperature measurement are based on the principle of heat equilibrium between the thermal sensor and the target location theoretically. However, the measurement position is not able to be definitely determined. In this study, a 2-dimensional mathematical model was built based upon some assumptions for the physiological condition of the human abdomen phantom. We evaluated the feasibility in estimating the internal organs temperature distribution from the readings of the temperature sensors arranged on the skin surface. It is a typical inverse heat conduction problem (IHCP), and is usually mathematically ill-posed. In this study, by integrating some physical and physiological a-priori information, we invoked the quasi-linear (QL) method to reconstruct the internal temperature distribution. The solutions of this method were improved by increasing the accuracy of the sensors and adjusting their arrangement on the outer surface, and eventually reached the state of converging at the best state accurately. This study suggests that QL method is able to reconstruct the internal temperature distribution in this phantom and might be worthy of a further study in an anatomical based model.
Year
DOI
Venue
2011
10.1109/IEMBS.2011.6090322
EMBC
Keywords
Field
DocType
temperature sensors,temperature measurement,biomedical measurement,physiological a priori information,human abdominal phantom,thermal sensor,inverse modeling,inverse problems,internal temperature distribution reconstruction,2d mathematical model,inverse heat conduction problem,physiological models,heat equilibrium,ihcp,quasilinear method,biothermics,physical a priori information,deep body temperature measurement,skin surface temperature sensors,ill posed problem,heat conduction,internal organ temperature distribution,noninvasive methods,measurement position,human abdomen phantom,biological organs,phantoms,2 dimensional,computer model,mathematical model,biological systems,body temperature,inverse problem,heating,computational modeling
Computer science,Imaging phantom,Inverse problem,Artificial intelligence,Thermal sensors,Thermal conductivity,Computer vision,Inverse,Mathematical optimization,Thermography,Acoustics,Thermal conduction,Temperature measurement
Conference
Volume
ISSN
ISBN
2011
1557-170X
978-1-4244-4122-8
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Ming Huang1128.04
Wenxi Chen22211.15