Tumor parameter estimation considering the body geometry by thermography

Implementation of non-invasive, non-contact, radiation-free thermal diagnostic tools requires an accurate correlation between surface temperature and interior physiology derived from living bio-heat phenomena. Such associations in the chest, forearm, and natural and deformed breasts have been investigated using finite element analysis (FEA), where the geometry and heterogeneity of an organ are accounted for by creating anatomically-accurate FEA models. The quantitative links are involved in the proposed evolutionary methodology for forecasting unknown Physio-thermo-biological parameters, including the depth, size and metabolic rate of the underlying nodule. A Custom Genetic Algorithm (GA) is tailored to parameterize a tumor by minimizing a fitness function. The study has employed the finite element method to develop simulated data sets and gradient matrix. Furthermore, simulated thermograms are obtained by enveloping the data sets with ±10% random noise.

[1]  S J González,et al.  Dynamic infrared imaging of cutaneous melanoma and normal skin in patients treated with BNCT. , 2009, Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine.

[2]  N M Sudharsan,et al.  An improved three-dimensional direct numerical modelling and thermal analysis of a female breast with tumour , 2001, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

[3]  Vikram Mohan,et al.  Fore Arm Circumference and Hand Length Predicts Maximal Hand Grip Strength among Malaysian Population , 2014 .

[4]  Joseph D. Bronzino,et al.  Medical Infrared Imaging , 2007 .

[5]  Michael Molls,et al.  Blood perfusion and microenvironment of human tumors : implications for clinical radiooncology , 1998 .

[6]  Zidong Wang,et al.  Inference of Nonlinear State-Space Models for Sandwich-Type Lateral Flow Immunoassay Using Extended Kalman Filtering , 2011, IEEE Transactions on Biomedical Engineering.

[7]  E.Y.K. Ng, N.M. Sudharsan.  Numerical uncertainty and perfusion induced instability in bioheat equation: its importance in thermographic interpretation , 2001, Journal of medical engineering & technology.

[8]  R. Lawson.  Implications of surface temperatures in the diagnosis of breast cancer. , 1956, Canadian Medical Association journal.

[9]  E.F.J. Ring,et al.  Progress in the measurement of human body temperature , 1998, IEEE Engineering in Medicine and Biology Magazine.

[10]  Ramana M. Pidaparti,et al.  Breast Tumor simulation and parameters estimation using evolutionary algorithms , 2008 .

[11]  Zidong Wang,et al.  A Hybrid EKF and Switching PSO Algorithm for Joint State and Parameter Estimation of Lateral Flow Immunoassay Models , 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[12]  Chakravarthy Balaji,et al.  A neural network based estimation of tumour parameters from a breast thermogram , 2010 .

[13]  H. H. Pennes.  Analysis of tissue and arterial blood temperatures in the resting human forearm. 1948. , 1948, Journal of applied physiology.

[14]  Aura Conci,et al.  Breast thermography from an image processing viewpoint: A survey , 2013, Signal Process..

[15]  M. Osman,et al.  Thermal modeling of the malignant woman's breast. , 1988, Journal of biomechanical engineering.

[16]  Jing Liu,et al.  Mathematical modeling of temperature mapping over skin surface and its implementation in thermal disease diagnostics , 2004, Comput. Biol. Medicine.

[17]  J. P. Agnelli,et al.  Tumor location and parameter estimation by thermography , 2011, Math. Comput. Model..

[18]  Jing Liu,et al.  Boundary information based diagnostics on the thermal states of biological bodies , 2000 .

[19]  Zidong Wang,et al.  Identification of Nonlinear Lateral Flow Immunoassay State-Space Models via Particle Filter Approach , 2012, IEEE Transactions on Nanotechnology.

[20]  M. Osman,et al.  Thermal modeling of the normal woman's breast. , 1984, Journal of biomechanical engineering.

[21]  Lawrence. Davis,et al.  Handbook Of Genetic Algorithms , 1990 .

[22]  F.A. Mohammadi,et al.  Development of an electrothermal simulation tool for integrated circuits: Application to a two-transistor circuit , 2008, Canadian Journal of Electrical and Computer Engineering.

[23]  M Gautherie,et al.  THERMOPATHOLOGY OF BREAST CANCER: MEASUREMENT AND ANALYSIS OF IN VIVO TEMPERATURE AND BLOOD FLOW , 1980, Annals of the New York Academy of Sciences.

[24]  Elaine P. Scott,et al.  Thermal Detection of Embedded Tumors using Infrared Imaging , 2007 .

[25]  Michael E Richards,et al.  Ultrasound determination of chest wall thickness: implications for needle thoracostomy. , 2011, The American journal of emergency medicine.

[26]  Minhua Zhou,et al.  Estimation of Temperature Distribution in Biological Tissue by Analytic Solutions of Pennes' Equation , 2009, 2009 2nd International Conference on Biomedical Engineering and Informatics.

[27]  E. Y. K. Ng,et al.  Surface Temperature Distribution of a Breast With and Without Tumour. , 1999, Computer methods in biomechanics and biomedical engineering.

[28]  R. Lawson,et al.  Breast Cancer and Body Temperature. , 1963, Canadian Medical Association journal.

[29]  Fan Yu,et al.  An analytic solution of one-dimensional steady-state Pennes’ bioheat transfer equation in cylindrical coordinates , 2004 .

[30]  S. Hossain,et al.  Neural network approach for the determination of heat source parameters from surface temperature image , 2011, 2011 24th Canadian Conference on Electrical and Computer Engineering(CCECE).