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Abstract #5094

Automatic Segmentation of Brain Tumors on Non-Contrast-Enhanced Magnetic Resonance Images Using Fuzzy Clustering

Yi-Min Liu1, Chun-Chih Liao1,2, Furen Xiao1,3, Jau-Min Wong1, I-Jen Chiang1,4

1Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan; 2Department of Neurosurgery, Taipei Hospital, Department of Health, Taipei, Taiwan; 3Department of Neurosurgery, National Taiwan University Hospital; 4Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan

An automated brain tumor segmentation method is desirable for helping human experts to obtain tumor location and volume estimation. This study was aimed to automatically segment brain tumor with two non-contrast-enhanced MR images, T1 and T2 images, via an unsupervised fuzzy c-means clustering method combined with region merging and knowledge-based analysis. The overall quantitative results percent match and correspondence ratio of this system are 0.842 and 0.716, respectively.