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ProbExplorer: Uncertainty‐guided Exploration and Editing of Probabilistic Medical Image Segmentation
Author(s) -
Saad Ahmed,
Möller Torsten,
Hamarneh Ghassan
Publication year - 2010
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2009.01691.x
Subject(s) - computer science , probabilistic logic , segmentation , visualization , rendering (computer graphics) , artificial intelligence , image segmentation , context (archaeology) , medical imaging , data mining , computer vision , machine learning , paleontology , biology
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.