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2015
DOI: 10.1177/1533034615580694
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Graphics Processing Unit-Based Bioheat Simulation to Facilitate Rapid Decision Making Associated with Cryosurgery Training

Abstract: This study focuses on the implementation of an efficient numerical technique for cryosurgery simulations on a graphics processing unit (GPU) as an alternative means to accelerate run time. This study is part of an ongoing effort to develop computerized training tools for cryosurgery, with prostate cryosurgery as a developmental model. The ability to perform rapid simulations of varying test cases is critical to facilitate sound decision making associated with medical training. Consistent with clinical practice… Show more

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Cited by 21 publications
(33 citation statements)
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“…The PFAM is computationally inexpensive, which required less than 0.5 s for any of the cases presented above. As described in [27], the TFRM is solved by applying a sparse matrix format and internal solvers for efficiency in calculations, with a typical runtime under 3 s. These runtime numbers represent non-optimized computation frameworks, where GPU implementation is likely to reduce the overall runtime to milliseconds [9]. Hence, the integrated numerical scheme is relevant for clinical practice and warrants further development.…”
Section: Resultsmentioning
confidence: 99%
“…The PFAM is computationally inexpensive, which required less than 0.5 s for any of the cases presented above. As described in [27], the TFRM is solved by applying a sparse matrix format and internal solvers for efficiency in calculations, with a typical runtime under 3 s. These runtime numbers represent non-optimized computation frameworks, where GPU implementation is likely to reduce the overall runtime to milliseconds [9]. Hence, the integrated numerical scheme is relevant for clinical practice and warrants further development.…”
Section: Resultsmentioning
confidence: 99%
“…Note that planning solutions were not given at the end of the pretest on the same cases. The applied thermal history was selected to simulate the cooling capabilities of Joule-Thomson based cryoprobes, as discussed in detail in (13,19). …”
Section: Methodsmentioning
confidence: 99%
“…Of the 17 residents, 12 (71%) were male, 5 (29%) were female, not by choice but due to the current demographics of the surgical residency program at AHN. All bioheat transfer simulations and defect calculations were performed with a recently developed, GPU-based code, with a typical runtime of a few seconds on personal workstations located at the Biothermal Technology Laboratory (BTTL), at Carnegie Mellon University (19). In order to make use of superior computation capabilities at the BTTL while benefiting from the unique educational environment at the STAR Center, human subject studies were performed by means of remote networking between the AHN and the BTTL, using a framework that further signifies the potential for internet-based training.…”
Section: Methodsmentioning
confidence: 99%
“…The majority of those efforts have focused on computation methods to plan the cryoprobe layout 6,7,812, , while more sporadic efforts addressed simulation of TRUST guidance 13 , prostate model reconstruction 14,15 , and acceleration of bioheat transfer simulations 16,17 . Unfortunately, since prostate cryosurgery is yet to be standardized, the computational means are yet to be reduced to practice.…”
Section: Introductionmentioning
confidence: 99%