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The most common primary brain tumors are gliomas, evolving from the cerebralsupportive cells. For clinical follow-up, the evaluation of the preoperativetumor volume is essential. Volumetric assessment of tumor volume with manualsegmentation of its outlines is a time-consuming process that can be overcomewith the help of computerized segmentation methods. In this contribution, twomethods for World Health Organization (WHO) grade IV glioma segmentation in thehuman brain are compared using magnetic resonance imaging (MRI) patient datafrom the clinical routine. One method uses balloon inflation forces, and relieson detection of high intensity tumor boundaries that are coupled with the useof contrast agent gadolinium. The other method sets up a directed and weightedgraph and performs a min-cut for optimal segmentation results. The ground truthof the tumor boundaries - for evaluating the methods on 27 cases - is manuallyextracted by neurosurgeons with several years of experience in the resection ofgliomas. A comparison is performed using the Dice Similarity Coefficient (DSC),a measure for the spatial overlap of different segmentation results.

A Comparison of Two Human Brain Tumor Segmentation Methods for MRI Data