<p>Different types of distances between diffusion tensors: (a) Euclidean metric, (b) J-divergence metric, (c) geodesic metric, (d) our learned metric.</p
<p>(a) non-linear metric VS. linear metrics. (b) multiple non-linear metrics VS. single non-linear m...
In order to extract geometric information from images, suitable operators must be constructed. After...
AbstractSimilarity and dissimilarity measures are widely used in many research areas and application...
Abstract. Diffusion tensor imaging has become an important research and clinical tool, owing to its ...
Abstract The measurement of the distance between diffusion tensors is the foun-dation on which any s...
Correlations of the tensor-based diffusion metrics (i.e., FA, MD) and NODDI-based diffusion metrics ...
Many different measures have been proposed to compute similarities and distances between diffusion t...
Multivariate Gaussian densities are pervasive in pattern recognition and machine learning. A central...
Abstract. In algorithms for processing diffusion tensor images, two common ingredients are interpola...
<p>(a) Earth Moving Distance in the Domains of Medicine and Physics (b) Earth Moving Distance in Dif...
Criteria for optimally discretizing measurable sets in Euclidean space is a difficult and old proble...
Many problems in operations research and in economics reduce to the finding of one or more points m...
One of the approaches in diffusion tensor imaging is to consider a Riemannian metric given by the in...
Introduction: Appropriate definition of the distance measure between diffusion tensors has a deep im...
In segmentation techniques for Diffusion Tensor Imaging (DTI) data, the similarity of diffusion tens...
<p>(a) non-linear metric VS. linear metrics. (b) multiple non-linear metrics VS. single non-linear m...
In order to extract geometric information from images, suitable operators must be constructed. After...
AbstractSimilarity and dissimilarity measures are widely used in many research areas and application...
Abstract. Diffusion tensor imaging has become an important research and clinical tool, owing to its ...
Abstract The measurement of the distance between diffusion tensors is the foun-dation on which any s...
Correlations of the tensor-based diffusion metrics (i.e., FA, MD) and NODDI-based diffusion metrics ...
Many different measures have been proposed to compute similarities and distances between diffusion t...
Multivariate Gaussian densities are pervasive in pattern recognition and machine learning. A central...
Abstract. In algorithms for processing diffusion tensor images, two common ingredients are interpola...
<p>(a) Earth Moving Distance in the Domains of Medicine and Physics (b) Earth Moving Distance in Dif...
Criteria for optimally discretizing measurable sets in Euclidean space is a difficult and old proble...
Many problems in operations research and in economics reduce to the finding of one or more points m...
One of the approaches in diffusion tensor imaging is to consider a Riemannian metric given by the in...
Introduction: Appropriate definition of the distance measure between diffusion tensors has a deep im...
In segmentation techniques for Diffusion Tensor Imaging (DTI) data, the similarity of diffusion tens...
<p>(a) non-linear metric VS. linear metrics. (b) multiple non-linear metrics VS. single non-linear m...
In order to extract geometric information from images, suitable operators must be constructed. After...
AbstractSimilarity and dissimilarity measures are widely used in many research areas and application...
DOI
Add to ORKG