Visibility-driven processing of streaming volume data

Veronika Solteszova, Åsmund Birkeland, Ivan Viola, Stefan Bruckner

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

In real-time volume data acquisition, such as 4D ultrasound, the raw data is challenging to visualize directly without additional processing. Noise removal and feature detection are common operations, but many methods are too costly to compute over the whole volume when dealing with live streamed data. In this paper, we propose a visibility-driven processing scheme for handling costly on-the-fly processing of volumetric data in real-time. In contrast to the traditional visualization pipeline, our scheme utilizes a fast computation of the potentially visible subset of voxels which significantly reduces the amount of data required to process. As filtering operations modify the data values which may affect their visibility, our method for visibility-mask generation ensures that the set of elements deemed visible does not change after processing. Our approach also exploits the visibility information for the storage of intermediate values when multiple operations are performed in sequence, and can therefore significantly reduce the memory overhead of longer filter pipelines. We provide a thorough technical evaluation of the approach and demonstrate it on several typical scenarios where on-the-fly processing is required.

Original languageEnglish (US)
Title of host publicationEurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2014
EditorsIvan Viola, Katja Buhler, Timo Ropinski
PublisherEurographics Association
Pages127-136
Number of pages10
ISBN (Electronic)9783905674620
DOIs
StatePublished - 2014
Event2014 Eurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2014 - Vienna, Austria
Duration: Sep 4 2014Sep 5 2014

Publication series

NameEurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2014

Conference

Conference2014 Eurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2014
Country/TerritoryAustria
CityVienna
Period09/4/1409/5/14

Bibliographical note

Funding Information:
This project has been partially funded by the Vienna Science and Technology Fund (WWTF) through project VRG11-010 and by EC Marie Curie Career Integration Grant through project PCIG13-GA-2013-618680. The authors thank also the MedViz network in Bergen and GE Vingmed Ultrasound for the support and Matej Mlejnek for providing the dataset Anna.

Funding Information:
This work has been carried out within the ISADAF project (In-Situ Adaptive Filtering, # 229352/O70) co-funded by the VERDIKT program of the Norwegian Research Council.

Publisher Copyright:
© Eurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2014. All rights reserved.

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Biomedical Engineering

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