Efficient Low-Resource Compression of HIFU Data
Loading...
Date
2018-06-26
Authors
Klepárník, Petr
Bařina, David
Zemčík, Pavel
Jaroš, Jiří
0000-0003-0311-3759Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Altmetrics
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.
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.
Description
Citation
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
en