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Volumetric Segmentation Using Weibull E-SD Fields
July-September 2003 (vol. 9 no. 3)
pp. 320-328
ASCII Text
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Jiuxiang Hu, Anshuman Razdan, Gregory M. Nielson, Gerald E. Farin, D. Page Baluch, David G. Capco, "Volumetric Segmentation Using Weibull E-SD Fields," IEEE Transactions on Visualization and Computer Graphics, vol. 9, no. 3, pp. 320-328, July-September, 2003.
 
 
BibTex
x
 
@article{ 10.1109/TVCG.2003.1207440,
author = {Jiuxiang Hu and Anshuman Razdan and Gregory M. Nielson and Gerald E. Farin and D. Page Baluch and David G. Capco},
title = {Volumetric Segmentation Using Weibull E-SD Fields},
journal ={IEEE Transactions on Visualization and Computer Graphics},
volume = {9},
number = {3},
issn = {1077-2626},
year = {2003},
pages = {320-328},
doi = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2003.1207440},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Visualization and Computer Graphics
TI - Volumetric Segmentation Using Weibull E-SD Fields
IS - 3
SN - 1077-2626
SP320
EP328
EPD - 320-328
A1 - Jiuxiang Hu,
A1 - Anshuman Razdan,
A1 - Gregory M. Nielson,
A1 - Gerald E. Farin,
A1 - D. Page Baluch,
A1 - David G. Capco,
PY - 2003
KW - 3D segmentation
KW - Weibull E-SD field
KW - noise index
KW - confocal laser scanning microscope
KW - CLSM.
VL - 9
JA - IEEE Transactions on Visualization and Computer Graphics
ER -
 

Abstract—This paper presents a coarse-grain approach for segmentation of objects with gray levels appearing in volume data. The input data is on a 3D structured grid of vertices $v(i,j,k) $, each associated with a scalar value. In this paper, we consider a voxel as a $\kappa\times\kappa\times \kappa$ cube and each voxel is assigned two values: expectancy and standard deviation (E-SD). We use the Weibull noise index to estimate the noise in a voxel and to obtain more precise E-SD values for each voxel. We plot the frequency of voxels which have the same E-SD, then 3D segmentation based on the Weibull E-SD field is presented. Our test bed includes synthetic data as well as real volume data from a confocal laser scanning microscope (CLSM). Analysis of these data all show distinct and defining regions in their E-SD fields. Under the guide of the E-SD field, we can efficiently segment the objects embedded in real and simulated 3D data.

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Index Terms:
3D segmentation, Weibull E-SD field, noise index, confocal laser scanning microscope, CLSM.
Citation:
Jiuxiang Hu, Anshuman Razdan, Gregory M. Nielson, Gerald E. Farin, D. Page Baluch, David G. Capco, "Volumetric Segmentation Using Weibull E-SD Fields," IEEE Transactions on Visualization and Computer Graphics, vol. 9, no. 3, pp. 320-328, July-Sept. 2003, doi:10.1109/TVCG.2003.1207440
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