[Research on Three-dimensional Temperature Field Reconstruction in Biological Tissue Based on Multi-island Genetic...

Area of Science:

• Biomedical Engineering
• Bio-heat Transfer
• Computational Modeling

Background:

• Accurate three-dimensional (3D) temperature field reconstruction in biological tissue is crucial for biomedical applications.
• Traditional methods often require extensive surface data and can be time-consuming.

Purpose of the Study:

• To develop and validate a novel, non-destructive method for 3D temperature field reconstruction in biological tissues.
• To transform the inverse problem of bio-heat transfer into a direct problem for efficient solving.

Main Methods:

• Utilized a multi-island genetic algorithm (MIGA) to solve the bio-heat transfer inverse problem.
• Employed a polypropylene material simulating fat tissue for experimental validation.
• Defined an objective function based on the absolute difference between experimental and simulated surface temperatures.

Main Results:

• The MIGA successfully reconstructed the 3D temperature field and identified heat source positions with high accuracy.
• Experimental and simulated heat source positions showed close approximation.
• The method confirmed the 3D temperature field and allowed for acquisition of arbitrary section temperature distributions.

Conclusions:

• The multi-island genetic algorithm (MIGA) provides a feasible and reliable method for non-destructive 3D temperature field reconstruction in biological tissues.
• This approach is convenient, fast, and does not necessitate complete surface data acquisition, unlike traditional numerical methods.
• The MIGA demonstrates significant potential for future applications in biomedical engineering and thermal analysis of tissues.