Plexiform Neurofibroma (PN) is a major complication of NeuroFibromatosis-1 (NF1), a common genetic disease
that involving the nervous system. PNs are peripheral nerve sheath tumors extending along the length of the
nerve in various parts of the body. Treatment decision is based on tumor volume assessment using MRI, which
is currently time consuming and error prone, with limited semi-automatic segmentation support. We present
in this paper a new method for the segmentation and tumor mass quantification of PN from STIR MRI scans.
The method starts with a user-based delineation of the tumor area in a single slice and automatically detects
the PN lesions in the entire image based on the tumor connectivity. Experimental results on seven datasets
yield a mean volume overlap difference of 25% as compared to manual segmentation by expert radiologist with
a mean computation and interaction time of 12 minutes vs. over an hour for manual annotation. Since the user
interaction in the segmentation process is minimal, our method has the potential to successfully become part of
the clinical workflow.
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