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Simulation Techniques for Cryosurgery


The ability to perform rapid cryosurgery simulations on a spectrum of test cases is critical to facilitate sound decision making associated with medical planning and training. It has been demonstrated recently that GPU-based computation, using C++ accelerated massive parallelism (AMP), enables simulation runtime 90 times faster than actual cryosurgical time, as shown below. Results are shown on already five years old machines, where actual simulation runtime is less than 2 seconds. This achievement is based on an efficient numerical scheme for cryosurgery simulations, which has been perfected for variable space intervals and time steps, using a parallelized computation framework, and an optimized GPU implementation.


Simulated-to-actual cryosurgery runtime ratio, for GPU-based (optimized) and CPU-based (parallelized and optimized) simulations on various platforms PubMed


Related work:

       Experimental verification of simulation techniques for cryosurgery

       Computerized planning of cryosurgery

       Computerized training tools for cryosurgery


Selected publications:

       Keelan, R., Zhang, H., Shimada, K., Rabin, Y. (2016):  GPU-based bioheat simulation to facilitate rapid decision making associated with cryosurgery training, Technology in Cancer Research and Treatment 15(2): 377-386 PubMed, HHS Public Access, Sage

       Keelan, R., Shimada, K., Rabin, Y. (2015): GPU-based simulation of ultrasound imaging artifacts for cryosurgery training, Technology in Cancer Research and Treatment, 16(1):5–14 PubMed, HHS Public Access, Sage

       Keelan, R., Yamakawa, S., Shimada, K., Rabin, Y. (2013): Computerized Training of cryosurgery – a system approach, CryoLetters 34(4):324-337 PubMed, HHS Public Access

       Rossi, M.R., Tanaka, D., Shimada, K., Rabin, Y. (2007): An efficient numerical technique for bioheat simulations and its application to computerized cryosurgery planning. Computer Methods and Programs in Biomedicine, 85(1):41-50 PubMed, HHS Public Access, BTTL Depository

       Rabin, Y., Shitzer, A. (1998): Numerical solution of the multidimensional freezing problem during cryosurgery. ASME Journal of Biomechanical Engineering, 120(1):32-37 PubMed, ASME Digital Collection, BTTL Depository




This research is supported, in part, by the National Cancer Institute, NIH Grant # 1R01CA134261