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Egger, J; Zukić, D; Freisleben, B; Kolb, A; Nimsky, C.
Segmentation of pituitary adenoma: a graph-based method vs. a balloon inflation method.
Comput Methods Programs Biomed. 2013; 110(3):268-278 Doi: 10.1016/j.cmpb.2012.11.010
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Egger Jan
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Abstract:
Among all abnormal growths inside the skull, the percentage of tumors in sellar region is approximately 10-15%, and the pituitary adenoma is the most common sellar lesion. A time-consuming process that can be shortened by using adequate algorithms is the manual segmentation of pituitary adenomas. In this contribution, two methods for pituitary adenoma segmentation in the human brain are presented and compared using magnetic resonance imaging (MRI) patient data from the clinical routine: Method A is a graph-based method that sets up a directed and weighted graph and performs a min-cut for optimal segmentation results: Method B is a balloon inflation method that uses balloon inflation forces to detect the pituitary adenoma boundaries. The ground truth of the pituitary adenoma boundaries - for the evaluation of the methods - are manually extracted by neurosurgeons. Comparison is done using the Dice Similarity Coefficient (DSC), a measure for spatial overlap of different segmentation results. The average DSC for all data sets is 77.5±4.5% for the graph-based method and 75.9±7.2% for the balloon inflation method showing no significant difference. The overall segmentation time of the implemented approaches was less than 4s - compared with a manual segmentation that took, on the average, 3.9±0.5min. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Find related publications in this database (using NLM MeSH Indexing)
Adenoma - pathology
Algorithms -
Computer Graphics -
Computer Simulation -
Humans -
Magnetic Resonance Imaging - methods
Magnetic Resonance Imaging - statistics & numerical data
Models, Anatomic -
Pituitary Neoplasms - pathology

Find related publications in this database (Keywords)
Segmentation
Pituitary adenoma
MRI
Graph-based
Balloon inflation
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