Compression, Segmentation, and Modeling of Filamentary Volumetric Data

McCormick, B.; Busse, B.; Doddapaneni, P.; Melek, Z.; Keyser, J.

Compression, Segmentation, and Modeling of Filamentary Volumetric Data

Files

333-338_mccormick.pdf (1.77 MB)

Date

2004

Authors

McCormick, B.
Busse, B.
Doddapaneni, P.
Melek, Z.
Keyser, J.

Publisher

The Eurographics Association

Abstract

We present a data structure for the representation of filamentary volumetric data, called the L-block. While the L-block can be used to represent arbitrary volume data sets, it is particularly geared towards representing long, thin, branching structures that prior volumetric representations have difficulty dealing with efficiently. The data structure is designed to allow for easy compression, storage, segmentation, and reconstruction of volumetric data such as scanned neuronal data. By ''polymerizing'' adjacent connected voxels into connected components, L-block construction facilitates real-time data compression and segmentation, as well as subsequent geometric modeling and visualization of embedded objects within the volume data set. We describe its application in the context of reconstruction of brain microstructure at a neuronal level of detail.

        @inproceedings{10.2312:sm.20041411
,
booktitle = {Solid Modeling
},
editor = {Gershon Elber and Nicholas Patrikalakis and Pere Brunet
},
title = {{Compression, Segmentation, and Modeling of Filamentary Volumetric Data
}},
author = {McCormick, B. and 
Busse, B. and 
Doddapaneni, P. and 
Melek, Z. and 
Keyser, J.
},
year = {2004
},
publisher = {The Eurographics Association
},
ISSN = {1811-7783
},
ISBN = {3-905673-55-X
},
DOI = {10.2312/sm.20041411
}
}