A Shape-Template Based Two-Stage Corpus Callosum Segmentation Technique for Sagittal Plane T1-Weighted Brain Magnetic Resonance Images
J.K. Mogali, N. Nallapareddy, C.S. Seelamantula, M. Unser
Proceedings of the 2013 Twentieth IEEE International Conference on Image Processing (ICIP'13), Melbourne VIC, Commonwealth of Australia, September 27-30, 2013, pp. 1177–1181.
We propose a semi-automatic technique to segment corpus callosum (CC) using a two-stage snake formulation: A restricted affine transform (RAT) constrained snake followed by an unconstrained snake in an iterative fashion. A statistical model is developed to capture the shape variations of CC from a training set, which restrict the unconstrained snake to lie in the shape-space of CC. The geometry of the constrained snake is optimized using a local contrast-based energy over RAT space (which allows for five degrees of freedom). On the other hand, the unconstrained snake is optimized using a unified energy (region, gradient, and curvature energy) formulation. Joint optimization resulted in increased robustness to initialization as well as fast and accurate segmentation. The technique was validated on 243 images taken from the OASIS database and performance was quantified using Jaccard's distance, sensitivity, and specificity as the metrics.
@INPROCEEDINGS(http://bigwww.epfl.ch/publications/mogali1301.html,
AUTHOR="Mogali, J.K. and Nallapareddy, N. and Seelamantula, C.S. and
Unser, M.",
TITLE="A Shape-Template Based Two-Stage Corpus Callosum Segmentation
Technique for Sagittal Plane {T1}-Weighted Brain Magnetic Resonance
Images",
BOOKTITLE="Proceedings of the 2013 Twentieth {IEEE} International
Conference on Image Processing ({ICIP'13})",
YEAR="2013",
editor="",
volume="",
series="",
pages="1177--1181",
address="Melbourne VIC, Commonwealth of Australia",
month="September 27-30,",
organization="",
publisher="",
note="")