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Biomedical subjects

Allen Tannenbaum

Publications and source records attributed to Allen Tannenbaum.

6 recordsLinked to original sources

Single nucleotide RNA choreography.

New structural analysis methods, and a tree formalism re-define and expand the RNA motif concept, unifying what previously appeared to be disparate groups of structures. We find RNA tetraloops at high frequencies, in new contexts, with unexpected lengths, and in novel topologies. The results, with broad implications for RNA structure in general, show that even at this most elementary level of organization, RNA tolerates astounding variation in conformation, length, sequence and context. However the variation is not random; it is well-described by four distinct modes, which are 3-2 switches (backbone topology variations), insertions, deletions and strand clips.

Models, Molecular↗

Despeckling of medical ultrasound images.

Speckle noise is an inherent property of medical ultrasound imaging, and it generally tends to reduce the image resolution and contrast, thereby reducing the diagnostic value of this imaging modality. As a result, speckle noise reduction is an important prerequisite, whenever ultrasound imaging is used for tissue characterization. Among the many methods that have been proposed to perform this task, there exists a class of approaches that use a multiplicative model of speckled image formation and take advantage of the logarithmical transformation in order to convert multiplicative speckle noise into additive noise. The common assumption made in a dominant number of such studies is that the samples of the additive noise are mutually uncorrelated and obey a Gaussian distribution. The present study shows conceptually and experimentally that this assumption is oversimplified and unnatural. Moreover, it may lead to inadequate performance of the speckle reduction methods. The study introduces a simple preprocessing procedure, which modifies the acquired radio-frequency images (without affecting the anatomical information they contain), so that the noise in the log-transformation domain becomes very close in its behavior to a white Gaussian noise. As a result, the preprocessing allows filtering methods based on assuming the noise to be white and Gaussian, to perform in nearly optimal conditions. The study evaluates performances of three different, nonlinear filters--wavelet denoising, total variation filtering, and anisotropic diffusion--and demonstrates that, in all these cases, the proposed preprocessing significantly improves the quality of resultant images. Our numerical tests include a series of computer-simulated and in vivo experiments.

Algorithms↗

Flux driven automatic centerline extraction.

We present a fast, robust and automatic method for computing centerline paths through tubular structures for application to virtual endoscopy. The key idea is to utilize a skeletonization algorithm which exploits properties of the average outward flux of the gradient vector field of a Euclidean distance function from the boundary of the structure. The algorithm is modified to yield a collection of 3D curves, each of which is locally centered. The approach requires no user interaction, is virtually parameter free and has low computational complexity. We validate the method quantitatively on a number of synthetic data sets with known centerlines and qualitatively on colon and vessel data segmented from CT and CRA images.

Algorithms↗

Flattening maps for the visualization of multibranched vessels.

In this paper, we present two novel algorithms which produce flattened visualizations of branched physiological surfaces, such as vessels. The first approach is a conformal mapping algorithm based on the minimization of two Dirichlet functionals. From a triangulated representation of vessel surfaces, we show how the algorithm can be implemented using a finite element technique. The second method is an algorithm which adjusts the conformal mapping to produce a flattened representation of the original surface while preserving areas. This approach employs the theory of optimal mass transport. Furthermore, a new way of extracting center lines for vessel fly-throughs is provided.

Algorithms↗

A statistically based flow for image segmentation.

In this paper we present a new algorithm for 3D medical image segmentation. The algorithm is versatile, fast, relatively simple to implement, and semi-automatic. It is based on minimizing a global energy defined from a learned non-parametric estimation of the statistics of the region to be segmented. Implementation details are discussed and source code is freely available as part of the 3D Slicer project. In addition, a new unified set of validation metrics is proposed. Results on artificial and real MRI images show that the algorithm performs well on large brain structures both in terms of accuracy and robustness to noise.

Algorithms↗

Automated identification of RNA conformational motifs: theory and application to the HM LSU 23S rRNA.

We develop novel methods for recognizing and cataloging conformational states of RNA, and for discovering statistical rules governing those states. We focus on the conformation of the large ribosomal subunit from Haloarcula marismortui. The two approaches described here involve torsion matching and binning. Torsion matching is a pattern-recognition code which finds structural repetitions. Binning is a classification technique based on distributional models of the data. In comparing the results of the two methods we have tested the hypothesis that the conformation of a very large complex RNA molecule can be described accurately by a limited number of discrete conformational states. We identify and eliminate extraneous and redundant information without losing accuracy. We conclude, as expected, that four of the torsion angles contain the overwhelming bulk of the structural information. That information is not significantly compromised by binning the continuous torsional information into a limited number of discrete values. The correspondence between torsion matching and binning is 99% (per residue). Binning, however, does have several advantages. In particular, we demonstrate that the conformation of a large complex RNA molecule can be represented by a small alphabet. In addition, the binning method lends itself to a natural graphical representation using trees.

Automation↗