User-Guided Segmentation of the Frontal Lobe
Using Fuzzy Rule-Based Active Contour Model
Yuji Fujiki, Syoji Kobashi, Katsuya Kondo, Yutaka Hata, Mieko Matsui*
Brain Function Research Institute, Inc.
Proc. of 1st Int. Conf. on Soft Computing and Intelligent Systems,
CD-ROM, (2002)
This paper describes a computer-aided system for
extracting the frontal lobe from 3-D human brain SPGR MR
images using fuzzy rule-based active contour model (ACM). The
volumetry and surface rendering of the frontal lobe are effective
for diagnosing the cerebral diseases with local atrophy. The
proposed system uses criterial curves consisting the central
sulcus and the sylvian fissure drawn by a user using proposed
graphical user interface (GUI). The criterial curves are
optimized by fuzzy rule-based ACM. The fuzzy rule-based ACM
can represent physiciansf knowledge with fuzzy if-then rules.
Using the optimized curves and the anterior and posterior
commissure (AC and PC), the frontal lobe is segmented
automatically. The experimental results showed that the
proposed system could segment the frontal lobe with high
accuracy.