• Publications
  • Influence
Partitioning 3D Surface Meshes Using Watershed Segmentation
This algorithm has applications for a variety of important problems in visualization and geometrical modeling including 3D feature extraction, mesh reduction, texture mapping 3D surfaces, and computer aided design. Expand
A Level-Set Approach to 3D Reconstruction from Range Data
  • R. Whitaker
  • Mathematics, Computer Science
  • International Journal of Computer Vision
  • 1 September 1998
This paper presents a method that uses the level sets of volumes to reconstruct the shapes of 3D objects from range data and presents an analytical characterization of the surface that maximizes the posterior probability, and presents a novel computational technique for level-set modeling, called the sparse-field algorithm. Expand
Curvature-based transfer functions for direct volume rendering: methods and applications
The proposed methodology combines an implicit formulation of curvature with convolution-based reconstruction of the field, and gives concrete guidelines for implementing the methodology, and illustrates the importance of choosing accurate filters for computing derivatives with Convolution. Expand
Microstructural connectivity of the arcuate fasciculus in adolescents with high-functioning autism
The results suggest that white matter microstructure in the arcuate fasciculus is affected in autism and that the language specialization apparent in the left arcuate of healthy subjects is not as evident in autism, which may be related to poorer language functioning. Expand
Unsupervised, information-theoretic, adaptive image filtering for image restoration
A novel unsupervised, information-theoretic, adaptive filter that improves the predictability of pixel intensities from their neighborhoods by decreasing their joint entropy and can thereby restore a wide spectrum of images. Expand
Manifold modeling for brain population analysis
The proposed method for building efficient representations of large sets of brain images is evaluated on the OASIS and ADNI brain databases of head MR images and shows that the manifold model is a statistically significant descriptor of clinical parameters. Expand
Exploring the retinal connectome
The first retinal connectome is described, validates the method, and provides key initial findings, which demonstrate that previously studied systems such as the AII amacrine cell network involve more network motifs than previously known. Expand
Contour Boxplots: A Method for Characterizing Uncertainty in Feature Sets from Simulation Ensembles
A generalization of functional data depth to contours is presented and methods for displaying the resulting boxplots for two-dimensional simulation data in weather forecasting and computational fluid dynamics are demonstrated. Expand
Adaptive Markov modeling for mutual-information-based, unsupervised MRI brain-tissue classification
The essential theoretical aspects underpinning adaptive, nonparametric Markov modeling and the theory behind the consistency of such a model are described. Expand
Rician Noise Removal in Diffusion Tensor MRI
A strategy for filtering diffusion tensor magnetic resonance images that accounts for Rician noise through a data likelihood term that is combined with a spatial smoothing prior and compares favorably with several other approaches from the literature. Expand