Pituitary Adenoma Volumetry with 3D Slicer

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Pituitary Adenoma Volumetry with 3D Slicer

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Title: Pituitary Adenoma Volumetry with 3D Slicer
Author: Egger, Jan; Kapur, Tina; Nimsky, Christopher; Kikinis, Ron

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Citation: Egger, Jan, Tina Kapur, Christopher Nimsky, and Ron Kikinis. 2012. Pituitary adenoma volumetry with 3D slicer. PLoS ONE 7(12): e51788.
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Abstract: In this study, we present pituitary adenoma volumetry using the free and open source medical image computing platform for biomedical research: (3D) Slicer. Volumetric changes in cerebral pathologies like pituitary adenomas are a critical factor in treatment decisions by physicians and in general the volume is acquired manually. Therefore, manual slice-by-slice segmentations in magnetic resonance imaging (MRI) data, which have been obtained at regular intervals, are performed. In contrast to this manual time consuming slice-by-slice segmentation process Slicer is an alternative which can be significantly faster and less user intensive. In this contribution, we compare pure manual segmentations of ten pituitary adenomas with semi-automatic segmentations under Slicer. Thus, physicians drew the boundaries completely manually on a slice-by-slice basis and performed a Slicer-enhanced segmentation using the competitive region-growing based module of Slicer named GrowCut. Results showed that the time and user effort required for GrowCut-based segmentations were on average about thirty percent less than the pure manual segmentations. Furthermore, we calculated the Dice Similarity Coefficient (DSC) between the manual and the Slicer-based segmentations to proof that the two are comparable yielding an average DSC of 81.97±3.39%.
Published Version: doi:10.1371/journal.pone.0051788
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3519899/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:10579574
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