Label Fusion Strategy Selection
Label fusion is used in medical image segmentation to combine several different labels of the same entity into a single discrete label, potentially more accurate, with respect to the exact, sought segmentation, than the best input element. Using simulated data, we compared three existing label fusio...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2012/431095 |
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| _version_ | 1850157880201707520 |
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| author | Nicolas Robitaille Simon Duchesne |
| author_facet | Nicolas Robitaille Simon Duchesne |
| author_sort | Nicolas Robitaille |
| collection | DOAJ |
| description | Label fusion is used in medical image segmentation to combine several different labels of the same entity into a single discrete label, potentially more accurate, with respect to the exact, sought segmentation, than the best input element. Using simulated data, we compared three existing label fusion techniques—STAPLE, Voting, and Shape-Based Averaging (SBA)—and observed that none could be considered superior depending on the dissimilarity between the input elements. We thus developed an empirical, hybrid technique called SVS, which selects the most appropriate technique to apply based on this dissimilarity. We evaluated the label fusion strategies on two- and three-dimensional simulated data and showed that SVS is superior to any of the three existing methods examined. On real data, we used SVS to perform fusions of 10 segmentations of the hippocampus and amygdala in 78 subjects from the ICBM dataset. SVS selected SBA in almost all cases, which was the most appropriate method overall. |
| format | Article |
| id | doaj-art-6277df7d199a49bcbec07f2b727704ca |
| institution | OA Journals |
| issn | 1687-4188 1687-4196 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Biomedical Imaging |
| spelling | doaj-art-6277df7d199a49bcbec07f2b727704ca2025-08-20T02:24:01ZengWileyInternational Journal of Biomedical Imaging1687-41881687-41962012-01-01201210.1155/2012/431095431095Label Fusion Strategy SelectionNicolas Robitaille0Simon Duchesne1Centre de Recherche de l'Institut Universitaire en Santé Mentale de Québec, 2601, Chemin de la Canardière, QC, G1J 2G3, CanadaCentre de Recherche de l'Institut Universitaire en Santé Mentale de Québec, 2601, Chemin de la Canardière, QC, G1J 2G3, CanadaLabel fusion is used in medical image segmentation to combine several different labels of the same entity into a single discrete label, potentially more accurate, with respect to the exact, sought segmentation, than the best input element. Using simulated data, we compared three existing label fusion techniques—STAPLE, Voting, and Shape-Based Averaging (SBA)—and observed that none could be considered superior depending on the dissimilarity between the input elements. We thus developed an empirical, hybrid technique called SVS, which selects the most appropriate technique to apply based on this dissimilarity. We evaluated the label fusion strategies on two- and three-dimensional simulated data and showed that SVS is superior to any of the three existing methods examined. On real data, we used SVS to perform fusions of 10 segmentations of the hippocampus and amygdala in 78 subjects from the ICBM dataset. SVS selected SBA in almost all cases, which was the most appropriate method overall.http://dx.doi.org/10.1155/2012/431095 |
| spellingShingle | Nicolas Robitaille Simon Duchesne Label Fusion Strategy Selection International Journal of Biomedical Imaging |
| title | Label Fusion Strategy Selection |
| title_full | Label Fusion Strategy Selection |
| title_fullStr | Label Fusion Strategy Selection |
| title_full_unstemmed | Label Fusion Strategy Selection |
| title_short | Label Fusion Strategy Selection |
| title_sort | label fusion strategy selection |
| url | http://dx.doi.org/10.1155/2012/431095 |
| work_keys_str_mv | AT nicolasrobitaille labelfusionstrategyselection AT simonduchesne labelfusionstrategyselection |