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 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. Categories and Subject Descriptors (according to ACM CCS): Computer Graphics [I.3.3]: Picture/Image Generation--Display algorithms

• Type: Journal
• Year: 2010
• Where: CGF
• Authors: Ahmed Saad, Torsten Möller, Ghassan Hamarneh
• Keywords: CGF 2010, Medical Imaging, Probabilistic Segmentation, Segmentation Editing Technique