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SPL Automated Segmentation of Brain Tumors Image Datasets

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Resource Type

  1. Software


  1. Resource Description
    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.
  2. Used by
    Surgical Planning Laboratory (BWH)
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Copyright © 2016 by the President and Fellows of Harvard College
The eagle-i Consortium is supported by NIH Grant #5U24RR029825-02 / Copyright 2016