ProbExplorer: Uncertainty-guided Exploration and Editing of Probabilistic Medical Image Segmentation

In this paper, we develop an interactive analysis and visualization tool for probabilistic segmentation results in medical imaging. We provide a systematic approach to analyze, interact and highlight regions of segmentation uncertainty. We introduce a set of visual analysis widgets integrating diffe...

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Veröffentlicht in:Computer graphics forum Jg. 29; H. 3; S. 1113 - 1122
Hauptverfasser: Saad, Ahmed, Möller, Torsten, Hamarneh, Ghassan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford, UK Blackwell Publishing Ltd 01.06.2010
Schlagworte:
C (programming language)
Computer graphics
Computer Graphics [I.3.3]: Picture/Image Generation-Display algorithms
Editing
Image segmentation
Medical imaging
Probabilistic methods
Probability
Probability theory
Rendering
Segmentation
Studies
ISSN:0167-7055, 1467-8659
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:In this paper, we develop an interactive analysis and visualization tool for probabilistic segmentation results in medical imaging. We provide a systematic approach to analyze, interact and highlight regions of segmentation uncertainty. We introduce a set of visual analysis widgets integrating different approaches to analyze multivariate probabilistic field data with direct volume rendering. We demonstrate the user's ability to identify suspicious regions (e.g. tumors) and correct the misclassification results using a novel uncertainty‐based segmentation editing technique. We evaluate our system and demonstrate its usefulness in the context of static and time‐varying medical imaging datasets.
Bibliographie:ark:/67375/WNG-JRC91C99-H
ArticleID:CGF1691
istex:3F64C886C2160FEABA6A408B6C474DDA79E882B5
SourceType-Scholarly Journals-1
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ISSN:0167-7055
1467-8659
DOI:10.1111/j.1467-8659.2009.01691.x