TY - JOUR
T1 - Output-Sensitive Filtering of Streaming Volume Data
AU - Solteszova, Veronika
AU - Birkeland, Åsmund
AU - Stoppel, Sergej
AU - Viola, Ivan
AU - Bruckner, Stefan
N1 - Funding Information:
This work has been supported by the MedViz lighthouse project IllustraSound and the ISADAF project (In-Situ Adaptive Filtering, #229352/O70) co-funded by the VERDIKT program of the Norwegian Research Council. The research was also partially supported by the Vienna Science and Technology Fund (WWTF) project VRG11-010 and by the EC Marie Curie Career Integration Grant project PCIG13-GA-2013-618680. Parts of this work have been made possible by the University of Bergen, the Bergen University Hospital, and Christian Michelsen Research AS through their strategic support of the MedViz program. The authors also thank GE Vingmed Ultrasound for the support and Matej Mlejnek for providing the dataset Anna. We also acknowledge the usage of Colorbrewer [BH15] for the color map in Figure.
Publisher Copyright:
© 2016 The Authors Computer Graphics Forum published by John Wiley & Sons Ltd.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - Real-time volume data acquisition poses substantial challenges for the traditional visualization pipeline where data enhancement is typically seen as a pre-processing step. In the case of 4D ultrasound data, for instance, costly processing operations to reduce noise and to remove artefacts need to be executed for every frame. To enable the use of high-quality filtering operations in such scenarios, we propose an output-sensitive approach to the visualization of streaming volume data. Our method evaluates the potential contribution of all voxels to the final image, allowing us to skip expensive processing operations that have little or no effect on the visualization. As filtering operations modify the data values which may affect the visibility, our main contribution is a fast scheme to predict their maximum effect on the final image. Our approach prioritizes filtering of voxels with high contribution to the final visualization based on a maximal permissible error per pixel. With zero permissible error, the optimized filtering will yield a result that is identical to filtering of the entire volume. We provide a thorough technical evaluation of the approach and demonstrate it on several typical scenarios that require on-the-fly processing.
AB - Real-time volume data acquisition poses substantial challenges for the traditional visualization pipeline where data enhancement is typically seen as a pre-processing step. In the case of 4D ultrasound data, for instance, costly processing operations to reduce noise and to remove artefacts need to be executed for every frame. To enable the use of high-quality filtering operations in such scenarios, we propose an output-sensitive approach to the visualization of streaming volume data. Our method evaluates the potential contribution of all voxels to the final image, allowing us to skip expensive processing operations that have little or no effect on the visualization. As filtering operations modify the data values which may affect the visibility, our main contribution is a fast scheme to predict their maximum effect on the final image. Our approach prioritizes filtering of voxels with high contribution to the final visualization based on a maximal permissible error per pixel. With zero permissible error, the optimized filtering will yield a result that is identical to filtering of the entire volume. We provide a thorough technical evaluation of the approach and demonstrate it on several typical scenarios that require on-the-fly processing.
KW - Categories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics] Three-Dimensional Graphics and Realism – Visible line/surface algorithms. I.4.3 [Image Processing and Computer Vision] Enhancement – Filtering
KW - object-order imaging
KW - visibility
KW - volume data processing
UR - http://www.scopus.com/inward/record.url?scp=84959525194&partnerID=8YFLogxK
U2 - 10.1111/cgf.12799
DO - 10.1111/cgf.12799
M3 - Article
C2 - 28356607
AN - SCOPUS:84959525194
VL - 36
SP - 249
EP - 262
JO - Computer Graphics Forum
JF - Computer Graphics Forum
SN - 0167-7055
IS - 1
ER -