Exploration and visualization of segmentation uncertainty using shape and appearance prior information
We develop an interactive analysis and visualization tool for probabilistic segmentation in medical imaging. The originality of our approach is that the data exploration is guided by shape and appearance knowledge learned from expert-segmented images of a training population. We introduce a set of m...
| Publié dans: | IEEE transactions on visualization and computer graphics. - 1996. - 16(2010), 6 vom: 15. Nov., Seite 1366-75 |
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| Auteur principal: | |
| Autres auteurs: | , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2010
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| Accès à la collection: | IEEE transactions on visualization and computer graphics |
| Sujets: | Journal Article Research Support, Non-U.S. Gov't |
| Résumé: | We develop an interactive analysis and visualization tool for probabilistic segmentation in medical imaging. The originality of our approach is that the data exploration is guided by shape and appearance knowledge learned from expert-segmented images of a training population. We introduce a set of multidimensional transfer function widgets to analyze the multivariate probabilistic field data. These widgets furnish the user with contextual information about conformance or deviation from the population statistics. We demonstrate the user's ability to identify suspicious regions (e.g. tumors) and to correct the misclassification results. We evaluate our system and demonstrate its usefulness in the context of static anatomical and time-varying functional imaging datasets |
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| Description: | Date Completed 14.12.2010 Date Revised 25.11.2016 published: Print Citation Status MEDLINE |
| ISSN: | 1941-0506 |
| DOI: | 10.1109/TVCG.2010.152 |