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.