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.
Assessing the accumulated stickiness magnitude from fabric–skin friction: effect of wetness level of various fabrics
