Efficient Low-Resource Compression of HIFU Data

Abstract

Large-scale numerical simulations of high-intensity focused ultrasound (HIFU), importantfor model-based treatment planning, generate large amounts of data. Typically, it is necessary to savehundreds of gigabytes during simulation. We propose a novel algorithm for time-varying simulationdata compression specialised for HIFU. Our approach is particularly focused on on-the-fly paralleldata compression during simulations. The algorithm is able to compress 3D pressure time seriesof 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 significantreduction of resources, such as storage space, network bandwidth, CPU time, and so forth, enablingbetter treatment planning using fast volume data visualisations. The paper describes the proposedmethod, its experimental evaluation, and comparisons to the state of the arts.Large-scale numerical simulations of high-intensity focused ultrasound (HIFU), importantfor model-based treatment planning, generate large amounts of data. Typically, it is necessary to savehundreds of gigabytes during simulation. We propose a novel algorithm for time-varying simulationdata compression specialised for HIFU. Our approach is particularly focused on on-the-fly paralleldata compression during simulations. The algorithm is able to compress 3D pressure time seriesof 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 significantreduction of resources, such as storage space, network bandwidth, CPU time, and so forth, enablingbetter treatment planning using fast volume data visualisations. The paper describes the proposedmethod, its experimental evaluation, and comparisons to the state of the arts.