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Wando Mount Pleasant Library
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Village Library
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St. Paul's/Hollywood Library
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Otranto Road Library
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Dorchester Road Library
9 a.m. - 8 p.m.
Phone: (843) 552-6466
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Phone: (843) 722-7550
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Phone: (843) 805-6930
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Can Atlas-Based Auto-Segmentation Ever Be Perfect? Insights From Extreme Value Theory.
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- Author(s): Schipaanboord, Bas; Boukerroui, Djamal; Peressutti, Devis; van Soest, Johan; Lustberg, Tim; Kadir, Timor; Dekker, Andre; van Elmpt, Wouter; Gooding, Mark
- Source:
IEEE Transactions on Medical Imaging. Jan2019, Vol. 38 Issue 1, p99-106. 8p.- Subject Terms:
- Source:
- Additional Information
- Abstract: Atlas-based segmentation is used in radiotherapy planning to accelerate the delineation of organs at risk (OARs). Atlas selection has been proposed to improve the performance of segmentation, assuming that the more similar the atlas is to the patient, the better the result. It follows that the larger the database of atlases from which to select, the better the results should be. This paper seeks to estimate a clinically achievable expected performance under this assumption. Assuming a perfect atlas selection, an extreme value theory has been applied to estimate the accuracy of single-atlas and multi-atlas segmentation given a large database of atlases. For this purpose, clinical contours of most common OARs on computed tomography of the head and neck (${N}=\textsf {316}$) and thoracic (${N}=\textsf {280}$) cases were used. This paper found that while for most organs, perfect segmentation cannot be reasonably expected, auto-contouring performance of a level corresponding to clinical quality could be consistently expected given a database of 5000 atlases under the assumption of perfect atlas selection. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of IEEE Transactions on Medical Imaging is the property of IEEE and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Abstract:
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