Abstract
Thickness of the cerebral cortex may provide valuable information about normal and abnormal neuroanatomy. For accurate cortical thickness measurements in brain MRI, precise segmentation of the grey matter border is necessary. In this paper we specifically address the problem of extracting the deep cortical folds or sulci, which can be difficult to resolve or totally obscured due to limited MRI resolution and contrast. We propose a method that iteratively solves Laplace’s equation for adjacent sub-layers of the cortex. This approach preserves the laminar structure of the cortex and provides clear definition of deep sulci. The implementation is computationally efficient. We present inter-subject and intra-subject results that are consistent with the literature.
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References
Geyer, S., Schleicher, A., Zilles, K.: Areas 3b, and 1 of Human Primary Somatosensory Cortex 1. Neuroimage 10 (1999) 63–83.
Meyer, J.R., Roychowdhury, S., Russell, E.J., Callahan, C., Gitelman, D., Mesulam, M.M.: Location of the central sulcus via cortical thickness of the precentral and postcentral gyri on MR. AJNR Am J Neuroradiol. 17 (1996) 1699–706.
Rusinek, H., de Leon, M.J., George, A.E., Stylopoulos, L.A., Chandra, R., Smith, G., Rand, T., Mourino, M., Kowalski, H. Alzheimer disease: measuring loss of cerebral gray matter with MR imaging Radiology 178 (1991) 109–114.
Terry, R.D., Peck, A., DeTeresa, R., Schecter, R., Horoupian, D.S.: Some morphometric aspects of the brain senile dementia of the Alzheimer type. An.. of Neuro.10(1981)184–192.
Stokking, R., Vincken, K.L., Viergever, M.A.: Automatic morphology-based brain segmentation (mbrase) from mri-T1 data. Neuroimage 12 (2000) 726–738.
Deichmann, R., Good, C.D., Josephs, O., Ashburner, J., Turner, R.: Optimization of 3-D MP-RAGE sequences for structural brain imaging. NeuroImage 12 (2000) 112–127.
Kruggel, F., Yves-von-Cramon, D.:Measuring the cortical thickness [MRI segmentation procedure] Proceedings Workshop on Mathematical Methods in Biomedical Image Analysis. IEEE Comput. Soc, Los Alamitos, CA, USA; (2000) 154–61.
MacDonald, D., Kabani, N., Avis, D., Evans, A.C.: Automated 3-D extraction of inner and outer surfaces of cerebral cortex from MRI. Neuroimage 12 (2000) 340–356.
Fischl, B., Dale, A..M.:Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci USA.97 (2000) 11050–5.
Jones, S.E., Buchbinder, B.R., Aharon, I.: Three-Dimensional Mapping of Cortical Thickness Using Laplace’s Equation. Human Brain Mapping 11 (2000) 12–32.
Ashburner, J., Friston, K.: Multimodal Image Coregistration and Partitioning-A Unified Framework. Neuroimage 6 (1997) 209–217.
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© 2002 Springer-Verlag Berlin Heidelberg
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Hutton, C., De Vita, E., Turner, R. (2002). Sulcal Segmentation for Cortical Thickness Measurements. In: Dohi, T., Kikinis, R. (eds) Medical Image Computing and Computer-Assisted Intervention — MICCAI 2002. MICCAI 2002. Lecture Notes in Computer Science, vol 2488. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45786-0_55
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DOI: https://doi.org/10.1007/3-540-45786-0_55
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