Biomedical subjects

Allen R Tannenbaum

Publications and source records attributed to Allen R Tannenbaum.

4 recordsLinked to original sources

PubMed2005

A Hamilton-Jacobi-Bellman approach to high angular resolution diffusion tractography.

This paper describes a new framework for white matter tractography in high angular resolution diffusion data. A direction-dependent local cost is defined based on the diffusion data for every direction on the unit sphere. Minimum cost curves are determined by solving the Hamilton-Jacobi-Bellman using an efficient algorithm. Classical costs based on the diffusion tensor field can be seen as a special case. While the minimum cost (or equivalently the travel time of a particle moving along the curve) and the anisotropic front propagation frameworks are related, front speed is related to particle speed through a Legendre transformation which can severely impact anisotropy information for front propagation techniques. Implementation details and results on high angular diffusion data show that this method can successfully take advantage of the increased angular resolution in high b-value diffusion weighted data despite lower signal to noise ratio.

Algorithms↗

PubMed2005

Harmonic skeleton guided evaluation of stenoses in human coronary arteries.

This paper presents a novel approach that three-dimensionally visualizes and evaluates stenoses in human coronary arteries by using harmonic skeletons. A harmonic skeleton is the center line of a multi-branched tubular surface extracted based on a harmonic function, which is the solution of the Laplace equation. This skeletonization method guarantees smoothness and connectivity and provides a fast and straightforward way to calculate local cross-sectional areas of the arteries, and thus provides the possibility to localize and evaluate coronary artery stenosis, which is a commonly seen pathology in coronary artery disease.

Algorithms↗

PubMed2005

Multiscale 3D shape analysis using spherical wavelets.

Shape priors attempt to represent biological variations within a population. When variations are global, Principal Component Analysis (PCA) can be used to learn major modes of variation, even from a limited training set. However, when significant local variations exist, PCA typically cannot represent such variations from a small training set. To address this issue, we present a novel algorithm that learns shape variations from data at multiple scales and locations using spherical wavelets and spectral graph partitioning. Our results show that when the training set is small, our algorithm significantly improves the approximation of shapes in a testing set over PCA, which tends to oversmooth data.

Algorithms↗

PubMed2004

The 3D structure of real polymer foams.

The intricate structure of polymeric foams may be examined using 3D imaging techniques such as MRI or X-ray tomography followed by image processing. Using a new 3D image processing technique, six images of polyurethane foams were analyzed to create computerized 3D models of the samples. Measurements on these models yielded distributions of many microstructural features, including strut length and window and cell shape distributions. Nearly 8000 struts, 4000 windows, and 376 cells were detected and measured in six polyurethane foam samples. When compared against previous theories and studies, these measurements showed that the structure of real polymeric foams differs significantly from both equilibrium models and aqueous foams. For example, previous studies of aqueous foams showed that about 70% of foam windows were pentagons. In the polymeric sample studied here, only 55% of windows were pentagonal.

Journal Article↗