Comput Methods Programs Biomed - Segmentation of pituitary adenoma: a graph-based method vs. a balloon inflation method.

Tópicos

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Resumo

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.

Resumo Limpo

among abnorm growth insid skull percentag tumor sellar region approxim pituitari adenoma common sellar lesion timeconsum process can shorten use adequ algorithm manual segment pituitari adenoma contribut two method pituitari adenoma segment human brain present compar use magnet reson imag mri patient data clinic routin method graphbas method set direct weight graph perform mincut optim segment result method b balloon inflat method use balloon inflat forc detect pituitari adenoma boundari ground truth pituitari adenoma boundari evalu method manual extract neurosurgeon comparison done use dice similar coeffici dsc measur spatial overlap differ segment result averag dsc data set graphbas method balloon inflat method show signific differ overal segment time implement approach less s compar manual segment took averag min

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