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A Learning Based Algorithm for Automatic Extraction of the Cortical Sulci
[chapter]
2006
Lecture Notes in Computer Science
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This paper presents a learning based method for automatic extraction of the major cortical sulci from MRI volumes or extracted surfaces. ...
Instead of using a few pre-defined rules such as the mean curvature properties, to detect the major sulci, the algorithm learns a discriminative model by selecting and combining features from a large pool ...
Acknowledgement This work was funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 RR021813 entitled Center for Computational Biology (CCB). ...
doi:10.1007/11866565_85
fatcat:gvmivnca6ffizcgrgye2puws5i
Automated Extraction of the Cortical Sulci Based on a Supervised Learning Approach
2007
IEEE Transactions on Medical Imaging
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This paper proposes a learning-based algorithm for automated extraction of the major cortical sulci from magnetic resonance imaging (MRI) volumes and cortical surfaces. ...
Unlike alternative methods for detecting the major cortical sulci, which use a small number of predefined rules based on properties of the cortical surface such as the mean curvature, our approach learns ...
CONCLUSION AND FUTURE WORK In this paper, we proposed a learning based algorithm for automatic detection of major cortical sulci. ...
doi:10.1109/tmi.2007.892506
pmid:17427741
fatcat:es6d4iznavckfjlougwoquaqpi
Joint Sulcal Detection on Cortical Surfaces With Graphical Models and Boosted Priors
2009
IEEE Transactions on Medical Imaging
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In this paper, we propose an automated approach for the joint detection of major sulci on cortical surfaces. ...
To make the inference tractable, a sample space with a finite number of candidate curves is automatically generated at each node based on the Hamilton-Jacobi skeleton of sulcal regions. ...
Sulcal Skeleton Extraction As a first stage toward sample space generation, we use the algorithm of computing Hamilton-Jacobi skeletons on cortical surfaces [35] to extract the skeleton of sulcal regions ...
doi:10.1109/tmi.2008.2004402
pmid:19244008
pmcid:PMC2754577
fatcat:qxc66v74pvblpewexuo2u2fx6q
Automatic Recognition of Cortical Sulci Using a Congregation of Neural Networks
[chapter]
2000
Lecture Notes in Computer Science
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This paper describes a complete system allowing automatic recognition of the main sulci of the human cortex. ...
A base of 26 brains manually labelled by a neuroanatomist is used to validate our approach. The whole system developed for the right hemisphere is made up of 265 neural networks. ...
The supervised learning of the experts relies on two kinds of examples. Correct examples extracted from the learning base must lead to the lowest output. ...
doi:10.1007/978-3-540-40899-4_5
fatcat:wvapleyufnhgtatuydu2z4zw64
Simultaneous cortical surface labeling and sulcal curve extraction
2012
Medical Imaging 2012: Image Processing
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Automatic labeling of the gyri and sulci on the cortical surface is important for studying cortical morphology and brain functions within populations. ...
a network of curves that form the boundary of gyral regions to the subject cortical surface. ...
For example, the first number in the column of S1 indicates that 70% of the points on the automatically extracted precentral sulcus are within a distance of 1.7 mm to the manually traced curve. ...
doi:10.1117/12.910552
pmid:27471339
pmcid:PMC4959948
dblp:conf/miip/YangCCP12
fatcat:elzg3ikthng7bbmvsk6zv2zpfa
Automatic labeling of cortical sulci using patch- or CNN-based segmentation techniques combined with bottom-up geometric constraints
2020
Medical Image Analysis
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The extreme variability of the folding pattern of the human cortex makes the recognition of cortical sulci, both automatic and manual, particularly challenging. ...
Reliable identification of the human cortical sulci in its entirety, is extremely difficult and is practiced by only a few experts. ...
(HBP's ramp-up phase), and from the FR-MDIC20161236445. ...
doi:10.1016/j.media.2020.101651
pmid:32163879
fatcat:5raatf4xbvft3m2kjrxwo3oeb4
Guest editorial: Special Issue on Computational Neuroanatomy
2007
IEEE Transactions on Medical Imaging
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Tu et al. report a related system for detecting the major cortical sulci in the brain, by learning a discriminative model using the probabilistic boosting tree algorithm. ...
of automatically extracted sulci (size, depth, etc.). ...
doi:10.1109/tmi.2007.895009
fatcat:6ud6g36ka5czpirs4vehlqiq5e
Co-registration of intra-operative brain surface photographs and pre-operative MR images
2014
International Journal of Computer Assisted Radiology and Surgery
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Methods: Automated classification of sulci on MRI extracted cortical surfaces was tested by comparison with user guided marking of prominent sulci on an intraoperative photography. ...
Results: User intervention was required for marking sulci on the photos demonstrating the potential for incorporating an automatic classifier. ...
The research herein was originally started while Benjamin Berkels was at the Institute for Numerical Simulation, University of Bonn, Germany and performed in part while he was holding a visiting position ...
doi:10.1007/s11548-014-0979-y
pmid:24477486
fatcat:lg6qfvri6bdw3genvfzhw6jgju
Cortical Shape Analysis in the Laplace-Beltrami Feature Space
[chapter]
2009
Lecture Notes in Computer Science
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A learning-based sulci detection algorithm is developed in this feature space to demonstrate its application in cortical shape analysis. ...
For the automated analysis of cortical morphometry, it is critical to develop robust descriptions of the position of anatomical structures on the convoluted cortex. ...
In section 3, we develop a learning-based sulci detection algorithm in the feature space to demonstrate its value in analyzing cortical anatomy. ...
doi:10.1007/978-3-642-04271-3_26
fatcat:drn3my7pyjf6hensu2pnivc6hi
Automatic sulcal curve extraction with MRF based shape prior
2012
2012 9th IEEE International Symposium on Biomedical Imaging (ISBI)
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In this paper, we present an automatic sulcal curve extraction method by registering a set of dense landmark points representing the sulcal curves to the subject cortical surface. ...
Our approach is validated using a leave-one-out strategy of training and evaluation on fifteen cortical surfaces, and a quantitative error analysis on the extracted major sulcal curves. ...
CONCLUSION We propose a method for automatically extracting the major sulcal curves by registering a set of dense landmark points to the subject cortical surface. ...
doi:10.1109/isbi.2012.6235573
pmid:27303593
pmcid:PMC4903163
fatcat:qc5rxm6d6bgzbncjit3ey4qct4
Exploring Cortical Folding Pattern Variability Using Local Image Features
[chapter]
2011
Lecture Notes in Computer Science
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In this paper, we present a data-driven technique for automatically learning cortical folding patterns from MR brain images. ...
The variability in cortical morphology across subjects makes it difficult to develop a general atlas of cortical sulci. ...
The main contribution of this paper is the introduction of an FBM technique for automatically learning new, unlabelled cortical folding patterns from a large set of subject brain images, attempting not ...
doi:10.1007/978-3-642-18421-5_5
fatcat:wlobew7pd5a6javjhxje2trl5y
Hamilton–Jacobi Skeleton on Cortical Surfaces
2008
IEEE Transactions on Medical Imaging
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In our approach, a cortical surface is first partitioned into sulcal and gyral regions via the solution of a variational problem using graph cuts, which can guarantee global optimality. ...
Compared with previous work that uses skeletons of 3D volumes to represent sulcal patterns, the skeletons on cortical surfaces can be easily decomposed into branches and provide a simpler way to construct ...
In our current work, we are developing a system for the automatic labeling of major sulci based on the method proposed in this paper. ...
doi:10.1109/tmi.2007.913279
pmid:18450539
pmcid:PMC2754588
fatcat:6ibv3kci6jd7nnv6fkyk4n2tmm
Cortical Surface Co-Registration based on MRI Images and Photos
[article]
2013
arXiv
pre-print
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The tools are a robust classification of sulci on MRI extracted cortical surfaces, guided user marking of most prominent sulci on a microscope image, and the actual variational registration method with ...
a fidelity energy for 3D deformations of the cortical surface combined with a higher order, linear elastica type prior energy. ...
On this background we here confine to a still manual marking of sulci by an expert who is supported by the results of a prior automatic pre-classification of sulci based on learned discriminative dictionaries ...
arXiv:1303.5691v1
fatcat:gjhxcjpdnbbopmtn6caq74to74
Hierarchical Isosurface Segmentation Based on Discrete Curvature
[article]
2003
EUROVIS 2005: Eurographics / IEEE VGTC Symposium on Visualization
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At a coarse level of detail, the algorithm detects the main features of the surface. ...
The surfaces are obtained from three-dimensional imaging data sets by isosurface extraction after data presmoothing and postprocessing the isosurfaces by a surface-growing algorithm. ...
LSSDSV) program under contract ACI 9982251, and through the National Partnership for Advanced Computational Infrastructure (NPACI); the National Institute of Mental Health and the National Science Foundation ...
doi:10.2312/vissym/vissym03/249-258
fatcat:aq3vqyxy2bf6rfzgyrox4diy5y
Co-Registration of Intra-Operative Photographs and Pre-Operative MR Images
[chapter]
2013
Bildverarbeitung für die Medizin 2013
Preserved Fulltext
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The tools are a robust classification of sulci on MRI extracted cortical surfaces, guided user marking of most prominent sulci on a microscope image, and the actual variational registration method with ...
a fidelity energy for 3D deformations of the cortical surface combined with a higher order, linear elastica type prior energy. ...
On this background we here confine to a still manual marking of sulci by an expert who is supported by the results of a prior automatic pre-classification of sulci based on learned discriminative dictionaries ...
doi:10.1007/978-3-642-36480-8_23
dblp:conf/bildmed/BerkelsCHRS13
fatcat:bnwoddqcu5b2nmuhmv2hmcmcsi
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