Seminars & Events

Mathematics and Computer Science
"Methods for Filamentarity Analysis of Three-Dimensional Data"

DATE: January 5, 2009 to January 5, 2009
TIME: 10:30 am
SPEAKER: Boris Efraty, Computational Biomedicine Lab, University of Houston
LOCATION: 221, A216
HOST: Ilya Safro

Description:
Advances in a modern technology enable researchers to easily acquire multi-channel three-dimensional images. On-going pioneering research in 3D image processing and visualization encompasses a broad spectrum of activities. However, processing, analyzing, and displaying these data can often be difficult and timeconsuming.

In this work we present some of the tools and techniques that are available to accomplish these tasks. This research focuses on a very specific type of data, which is typically very noisy and may contain filamentary faint structures such
as line segments and smooth curves. These tools mainly rely on the 3-D Beamlet Transform offering the collection
of line integrals along a strategic multi-scale set of line segments — the Beamlet set (running through the image at different orientations, positions and lengths).

Our research focuses on the following objectives: development of algorithms for computation of the beamlet transform, developing tools for efficient signal representation, studying the beamlet dictionary approximation properties for image classification by filamentary characteristics, and development of feature detection algorithms.

These tools and methods can be applied in a wide variety of application fields that involve 3D imaging. In this work we focus on applying Beamlet methods for the problem of dim target multi-frame detection and develop specialized tools for this application. We use tools from Graph theory and apply them to the special graph generated by the beamlets set.

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