University of Bergen | Faculty of Mathematics and Natural Sciences | Department of Informatics | Visualization Group
Visualization
You are here: Department of Informatics > Visualization Group > Team > Stefan Bruckner > Publications > Karimov-2015-GVE
 Visualization
 > about
 > team & contact info
 --- >  Stefan Bruckner
 > research
 > publications
 > projects
 > teaching
 > resources
 > network
 > events
 > links

Guided Volume Editing based on Histogram Dissimilarity

Alexey Karimov, Gabriel Mistelbauer, Thomas Auzinger, Stefan Bruckner

JOURNAL ARTICLE: Computer Graphics Forum, vol. 34, no. 3, pp. 91–100, 2015. DOI: 10.1111/cgf.12621

Abstract

Segmentation of volumetric data is an important part of many analysis pipelines, but frequently requires manual inspection and correction. While plenty of volume editing techniques exist, it remains cumbersome and error-prone for the user to find and select appropriate regions for editing. We propose an approach to improve volume editing by detecting potential segmentation defects while considering the underlying structure of the object of interest. Our method is based on a novel histogram dissimilarity measure between individual regions, derived from structural information extracted from the initial segmentation. Based on this information, our interactive system guides the user towards potential defects, provides integrated tools for their inspection, and automatically generates suggestions for their resolution. We demonstrate that our approach can reduce interaction effort and supports the user in a comprehensive investigation for high-quality segmentations.

Published

Computer Graphics Forum

Documents and Links

  • paper
  • www

Additional Media

  • Click to view
  • Click to view

BibTeX

@ARTICLE{Karimov-2015-GVE,
  author = {Alexey Karimov and Gabriel Mistelbauer and Thomas Auzinger and Stefan
	Bruckner},
  title = {Guided Volume Editing based on Histogram Dissimilarity},
  journal = {Computer Graphics Forum},
  year = {2015},
  volume = {34},
  pages = {91--100},
  number = {3},
  month = may,
  abstract = {Segmentation of volumetric data is an important part of many analysis
	pipelines, but frequently requires manual inspection and correction.
	While plenty of volume editing techniques exist, it remains cumbersome
	and error-prone for the user to find and select appropriate regions
	for editing. We propose an approach to improve volume editing by
	detecting potential segmentation defects while considering the underlying
	structure of the object of interest. Our method is based on a novel
	histogram dissimilarity measure between individual regions, derived
	from structural information extracted from the initial segmentation.
	Based on this information, our interactive system guides the user
	towards potential defects, provides integrated tools for their inspection,
	and automatically generates suggestions for their resolution. We
	demonstrate that our approach can reduce interaction effort and supports
	the user in a comprehensive investigation for high-quality segmentations.},
  doi = {10.1111/cgf.12621},
  event = {EuroVis 2015},
  keywords = {medical visualization, segmentation, volume editing, interaction},
  location = {Cagliari, Italy},
  owner = {bruckner},
  timestamp = {2015.06.08},
  url = {http://www.cg.tuwien.ac.at/research/publications/2015/karimov-2015-HD/}
}






 Last Modified: Stefan Bruckner, 2017-10-13