TY - JOUR
T1 - Finding parametric representations of the cortical sulci using an active contour model
AU - Vaillant, Marc
AU - Davatzikos, Christos
N1 - Funding Information:
The authors would like to thank R. Nick Bryan for his encouragement and support of this work, Mike Kraut for the fMRI data acquisition and Dzung Pham for providing the C-code implementing the fuzzy C-means algorithm. We also thank Fred Bookstein for an insightful discussion during the initial development of this work and the anonymous reviewers whose comments helped to improve this paper. This work was partially supported by a Whitaker grant to C. D. and by the NIH grant RO1-AG-3–2124 under the Human Brain Project.
PY - 1997
Y1 - 1997
N2 - The cortical sulci are brain structures resembling thin convoluted ribbons embedded in three dimensions. The importance of the sulci lies primarily in their relation to the cytoarchitectonic and functional organization of the underlying cortex and in their utilization as features in non-rigid registration methods. This paper presents a methodology for extracting parametric representations of the cerebral sulci from magnetic resonance images. The proposed methodology is based on deformable models utilizing characteristics of the cortical shape. Specifically, a parametric representation of a sulcus is determined by the motion of an active contour along the medial surface of the corresponding cortical fold. The active contour is initialized along the outer boundary of the brain and deforms toward the deep root of a sulcus under the influence of an external force field, restricting it to lie along the medial surface of the particular cortical fold. A parametric representation of the medial surface of the sulcus is obtained as the active contour traverses the sulcus. Based on the first fundamental form of this representation, the location and degree of an interruption of a sulcus can be readily quantified; based on its second fundamental form, shape properties of the sulcus can be determined. This methodology is tested on magnetic resonance images and it is applied to three medical imaging problems: quantitative morphological analysis of the central sulcus; mapping of functional activation along the primary motor cortex and non-rigid registration of brain images.
AB - The cortical sulci are brain structures resembling thin convoluted ribbons embedded in three dimensions. The importance of the sulci lies primarily in their relation to the cytoarchitectonic and functional organization of the underlying cortex and in their utilization as features in non-rigid registration methods. This paper presents a methodology for extracting parametric representations of the cerebral sulci from magnetic resonance images. The proposed methodology is based on deformable models utilizing characteristics of the cortical shape. Specifically, a parametric representation of a sulcus is determined by the motion of an active contour along the medial surface of the corresponding cortical fold. The active contour is initialized along the outer boundary of the brain and deforms toward the deep root of a sulcus under the influence of an external force field, restricting it to lie along the medial surface of the particular cortical fold. A parametric representation of the medial surface of the sulcus is obtained as the active contour traverses the sulcus. Based on the first fundamental form of this representation, the location and degree of an interruption of a sulcus can be readily quantified; based on its second fundamental form, shape properties of the sulcus can be determined. This methodology is tested on magnetic resonance images and it is applied to three medical imaging problems: quantitative morphological analysis of the central sulcus; mapping of functional activation along the primary motor cortex and non-rigid registration of brain images.
KW - Atlas
KW - Brain mapping
KW - Deformable models
KW - Non-rigid registration
KW - Sulci
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U2 - 10.1016/S1361-8415(97)85003-7
DO - 10.1016/S1361-8415(97)85003-7
M3 - Article
C2 - 9873912
AN - SCOPUS:0031215693
SN - 1361-8415
VL - 1
SP - 295
EP - 315
JO - Medical image analysis
JF - Medical image analysis
IS - 4
ER -