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SPL Automated Segmentation of Brain Tumors Image Datasets
eagle-i ID
http://harvard.eagle-i.net/i/0000012d-9fd7-70b6-4882-b08d80000000
Resource Type
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Resource Description
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An automated brain tumor segmentation method was developed and validated against manual segmentation with three-dimensional magnetic resonance images in 10 patients with meningiomas and low-grade gliomas, Kaus et al., 2001. The automated method (operator time, 5-10 minutes) allowed rapid identification of brain and tumor tissue with an accuracy and reproducibility comparable to those of manual segmentation (operator time, 3-5 hours), making automated segmentation practical for low-grade gliomas and meningiomas. We make available the image datasets used in our study, results of our algorithms, and open source software (3D Slicer) for data access and processing to interested parties, as a free service.
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Used by
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Surgical Planning Laboratory (BWH)
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Website(s)
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http://www.spl.harvard.edu/publications/item/view/1180
