EPFL | Biomedical Imaging Group | Brain Segmentation

Automated Connectivity-Based Thresholding Segmentation of Midsagittal Brain MR Images

C. Lee, M. Unser, T.A. Ketter

Proceedings of the SPIE Conference on Visual Communication and Image Processing: Wavelets and Fractals (VCIP'96), Orlando FL, USA, March 17-20, 1996, vol. 2727, part II, pp. 713–724.

In this paper, we propose an algorithm for automated segmentation of midsagittal brain MR images. First, we apply thresholding to obtain binary images. From the binary images, we locate some landmarks. Based on the landmarks and anatomical information, we preprocess the binary images to eliminate small regions and remove the skull, which substantially simplifies the subsequent operations. We perform segmentation in the binary image as much as possible and then return to the gray scale image to solve problematic areas. We propose a new connectivity-based thresholding segmentation to separate brain regions from surrounding tissues. Experiments show promising results.

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AUTHOR="Lee, C. and Unser, M. and Ketter, T.A.",
TITLE="Automated Connectivity-Based Thresholding Segmentation of
	Midsagittal Brain {MR} Images",
BOOKTITLE="Proceedings of the {SPIE} Conference on Visual
	Communication and Image Processing: {W}avelets and Fractals
	({VCIP'96})",
YEAR="1996",
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volume="2727",
series="",
pages="713--724",
address="Orlando FL, USA",
month="March 17-20,",
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note="Part {II}")

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