Efficient Low-Resource Compression of HIFU Data
AbstractLarge-scale numerical simulations of high-intensity focused ultrasound (HIFU), important for model-based treatment planning, generate large amounts of data. Typically, it is necessary to save hundreds of gigabytes during simulation. We propose a novel algorithm for time-varying simulation data compression specialised for HIFU. Our approach is particularly focused on on-the-fly parallel data compression during simulations. The algorithm is able to compress 3D pressure time series of linear and non-linear simulations with very acceptable compression ratios and errors (over 80% of the space can be saved with an acceptable error). The proposed compression enables significant reduction of resources, such as storage space, network bandwidth, CPU time, and so forth, enabling better treatment planning using fast volume data visualisations. The paper describes the proposed method, its experimental evaluation, and comparisons to the state of the arts. View Full-Text
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Kleparnik, P.; Barina, D.; Zemcik, P.; Jaros, J. Efficient Low-Resource Compression of HIFU Data. Information 2018, 9, 155.
Kleparnik P, Barina D, Zemcik P, Jaros J. Efficient Low-Resource Compression of HIFU Data. Information. 2018; 9(7):155.Chicago/Turabian Style
Kleparnik, Petr; Barina, David; Zemcik, Pavel; Jaros, Jiri. 2018. "Efficient Low-Resource Compression of HIFU Data." Information 9, no. 7: 155.
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