Abstract. We propose in this work a novel variational method for computing maps between surfaces by combining informative geometric features and regularizing forces including inver...
Arthur W. Toga, Jonathan H. Morra, Paul M. Thompso...
The evaluation of the quality of segmentations of an image, and the assessment of intra- and inter-expert variability in segmentation performance, has long been recognized as a dic...
Abstract. Four-dimensional respiratory correlated computed tomography (4D RCCT) has been widely used for studying organ motion. Most current algorithms use binning techniques which...
Jacob Hinkle, P. Thomas Fletcher, Brian Wang, Bill...
We propose a novel Bayesian registration formulation in which image location is represented as a latent random variable. Location is marginalized to determine the maximum a priori ...
We present a novel framework for characterizing signals in images using techniques from computational algebraic topology. This technique is general enough for dealing with noisy mu...
Recently, marginal space learning (MSL) was proposed as a generic approach for automatic detection of 3D anatomical structures in many medical imaging modalities [1]. To accurately...
Abstract. Image segmentation in microscopy, especially in interferencebased optical microscopy modalities, is notoriously challenging due to inherent optical artifacts. We propose ...
The purpose of this paper is to measure the variability of a population of white matter fiber bundles without imposing unrealistic geometrical priors. In this respect, modeling fib...
Stanley Durrleman, Pierre Fillard, Xavier Pennec, ...
In this paper, we propose a new nonparametric Bayesian framework to cluster white matter fiber tracts into bundles using a hierarchical Dirichlet processes mixture (HDPM) model. Th...
Carl-Fredrik Westin, W. Eric L. Grimson, Xiaogang ...
We describe a technique to simultaneously estimate a local neural fiber model and trace out its path. Existing techniques estimate the local fiber orientation at each voxel indepen...
James G. Malcolm, Martha Elizabeth Shenton, Yogesh...