Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Convergence Properties of the Nelder--Mead Simplex Method in Low Dimensions
SIAM Journal on Optimization
Thalamus segmentation from diffusion tensor magnetic resonance imaging
Journal of Biomedical Imaging
Probabilistic clustering and quantitative analysis of white matter fiber tracts
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
Nonlinear registration of diffusion MR images based on fiber bundles
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
White matter tract clustering and correspondence in populations
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Automated atlas-based clustering of white matter fiber tracts from DTMRI
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Knowledge-Based classification of neuronal fibers in entire brain
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
High-Dimensional white matter atlas generation and group analysis
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Segmentation of thalamic nuclei from DTI using spectral clustering
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Efficient population registration of 3d data
CVBIA'05 Proceedings of the First international conference on Computer Vision for Biomedical Image Applications
The structural clustering and analysis of metric based on granular space
Pattern Recognition
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We propose an integrated registration and clustering algorithm, called "consistency clustering", that automatically constructs a probabilistic white-matter atlas from a set of multi-subject diffusion weighted MR images. We formulate the atlas creation as a maximum likelihood problem which the proposed method solves using a generalized Expectation Maximization (EM) framework. Additionally, the algorithm employs an outlier rejection and denoising strategy to produce sharp probabilistic maps of certain bundles of interest. We test this algorithm on synthetic and real data, and evaluate its stability against initialization. We demonstrate labeling a novel subject using the resulting spatial atlas and evaluate the accuracy of this labeling. Consistency clustering is a viable tool for completely automatic white-matter atlas construction for sub-populations and the resulting atlas is potentially useful for making diffusion measurements in a common coordinate system to identify pathology related changes or developmental trends.