Cryosurgery is a medical technique to destroy unwanted tissue using extreme low temperature from a medium conducted using one or some cryoprobes with an minimum risk. Conventionally the configuration of cryoprobes (the number of cryoprobes and how to place them) has been applied using experience from trial and error methods of the cryosurgeon, so that it requires a method to optimize the configuration - to maximize the destruction of a target region while minimizing the destruction of surrounding healthy tissues. In this study, the heat transfer occurred in cryosurgery process is categorized as Stefan problem and simulated using finite volume scheme. Cryoprobe placement is optimized using deterministic displacement procedure based on the notion of force-field analogy. The optimization algorithm is evaluated to test some simple cases and complex-shaped geometry. The test cases are evaluated using perfect circle target with 4 different initial placements. Moreover, the algorithm is applied to the lung cancer geometry with the initial placement is obtained from bubble packing method. All different configurations are conducted using 4 to 14 cryoprobes. The simulation results show that the algorithm yields total defect average of 2.5% for circular geometry test cases and 3.68% for lung cancer with complex-shaped.
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