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

Abstract

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.

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Additional Information

(48 out of 164 accepted; 4 citations)

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Authors
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Supplemental Material
Citation
Category
Journal Paper
Divisions
Visualization and Data Analysis
Journal or Publication Title
Computer Graphics Forum: the international journal of the Eurographics Association
ISSN
-
Page Range
pp. 1113-1122
Number
3
Volume
29
Date
June 2010
Official URL
http://www.cs.sfu.ca/~torsten/Publications/Papers/...
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