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Research Papers

Procedure to Estimate Thermophysical and Geometrical Parameters of Embedded Cancerous Lesions Using Thermography

[+] Author and Article Information
Jose Manuel Luna

 University of Guanajuato, Department of Mechanical Engineering, Apartado Postal 215A, 36730, Salamanca, GTO., Mexicojm.luna.1980@gmail.com

Ricardo Romero-Mendez

 Autonomous University of San Luis Potosi, School of Engineering, Dr. Manuel Nava 8, 78290, San Luis Potosi, SLP., Mexicorromerom@uaslp.mx

Abel Hernandez-Guerrero1

 University of Guanajuato, Department of Mechanical Engineering, Apartado Postal 215A, 36730, Salamanca, GTO., Mexicoabel@ugto.mx

Francisco Elizalde-Blancas

 University of Guanajuato, Department of Mechanical Engineering, Apartado Postal 215A, 36730, Salamanca, GTO., Mexicofranciscoeb@ugto.mx

1

Corresponding author.

J Biomech Eng 134(3), 031008 (Mar 27, 2012) (9 pages) doi:10.1115/1.4006197 History: Received June 16, 2011; Revised February 10, 2012; Accepted February 16, 2012; Posted February 24, 2012; Published March 26, 2012; Online March 27, 2012

Based on the fact that malignant cancerous lesions (neoplasms) develop high metabolism and use more blood supply than normal tissue, infrared thermography (IR) has become a reliable clinical technique used to indicate noninvasively the presence of cancerous diseases, e.g., skin and breast cancer. However, to diagnose cancerous diseases by IR, the technique requires procedures that explore the relationship between the neoplasm characteristics (size, blood perfusion rate and heat generated) and the resulting temperature distribution on the skin surface. In this research work the dual reciprocity boundary element method (DRBEM) has been coupled with the simulated annealing technique (SA) in a new inverse procedure, which coupled to the IR technique, is capable of estimating simultaneously geometrical and thermophysical parameters of the neoplasm. The method is of an evolutionary type, requiring random initial values for the unknown parameters and no calculations of sensitivities or search directions. In addition, the DRBEM does not require any re-meshing at each proposed solution to solve the bioheat model. The inverse procedure has been tested considering input data for simulated neoplasms of different sizes and positions in relation to the skin surface. The successful estimation of unknown neoplasm parameters validates the idea of using the SA technique and the DRBEM in the estimation of parameters. Other estimation techniques, based on genetic algorithms or sensitivity coefficients, have not been capable of obtaining a solution because the skin surface temperature difference is very small.

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Copyright © 2012 by American Society of Mechanical Engineers
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Figures

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Figure 1

Neoplasm of different sizes and positions embedded in healthy tissue

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Figure 2

Multidomain used for the application of the DRBEM

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Figure 3

Skin surface temperature distribution for healthy and infected tissues

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Figure 4

Variation of skin surface temperature for all the neoplasm of Fig. 1

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Figure 5

Procedure of the inverse algorithm

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Figure 6

Variation between the recovered and input skin surface temperature distributions

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Figure 7

Search course for the xc parameter

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Figure 8

Search course for the yc parameter

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Figure 9

Search course for the normalized neoplasm size

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Figure 10

Search course for the neoplasm blood perfusion rate

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Figure 11

Search course for the neoplasm metabolic heat generation

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Figure 12

Convergence course and temperature decrease of the annealing process

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Figure 13

Perturbed skin surface temperature

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