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M. Choi, M. Jang, G. Noh, "A Deep Learning Based Real-Time Computational Method for Transcranial Focused Ultrasound Guidance System", in B.H.V. Topping, P. Iványi, (Editors), "Proceedings of the Eleventh International Conference on Engineering Computational Technology", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 2, Paper 6.1, 2022, doi:10.4203/ccc.2.6.1

Keywords: deep neural network, surrogate model, wave propagation, transcranial focused ultrasound, finite-difference time-domain, real-time.

Abstract

In this paper, we present a method for surrogate model of transcranial focused ultrasound (tFUS) propagation problem using deep learning technique. The trained neural network outputs an acoustic source position of transducer placement. The training datasets are generated by forward tFUS simulation using finite-difference time-domain method. The performance of the proposed method was evaluated through three examples of ex vivo human calvaria. The results show that the deep learning based model can provide an accurate acoustic field solution in real-time. Through this study, we proved the effectiveness of the deep-learning based surrogate model of tFUS propagation problem and its applicability in practical clinics.

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Front Page Browse CCC CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Conferences ISSN 2753-3239 CCC: 2 PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON ENGINEERING COMPUTATIONAL TECHNOLOGY Edited by: B.H.V. Topping and P. Iványi Paper 6.1 A Deep Learning Based Real-Time Computational Method for Transcranial Focused Ultrasound Guidance System M. Choi, M. Jang and G. Noh School of Mechanical Engineering, Korea University, Seoul, South Korea doi:10.4203/ccc.2.6.1 Full Bibliographic Reference for this paper M. Choi, M. Jang, G. Noh, "A Deep Learning Based Real-Time Computational Method for Transcranial Focused Ultrasound Guidance System", in B.H.V. Topping, P. Iványi, (Editors), "Proceedings of the Eleventh International Conference on Engineering Computational Technology", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 2, Paper 6.1, 2022, doi:10.4203/ccc.2.6.1 Keywords: deep neural network, surrogate model, wave propagation, transcranial focused ultrasound, finite-difference time-domain, real-time. Abstract In this paper, we present a method for surrogate model of transcranial focused ultrasound (tFUS) propagation problem using deep learning technique. The trained neural network outputs an acoustic source position of transducer placement. The training datasets are generated by forward tFUS simulation using finite-difference time-domain method. The performance of the proposed method was evaluated through three examples of ex vivo human calvaria. The results show that the deep learning based model can provide an accurate acoustic field solution in real-time. Through this study, we proved the effectiveness of the deep-learning based surrogate model of tFUS propagation problem and its applicability in practical clinics. download the full-text of this paper (PDF, 5 pages, 299 Kb) go to the previous paper go to the next paper return to the table of contents return to the volume description
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