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Digital Image Computing: Techniques and Applications (DICTA'05)
A New Segmentation Method for Lung HRCT Images
Cairns, Australia
December 06-December 08
ISBN: 0-7695-2467-2
ASCII Text
x 
 
Rahil Garnavi, Ahmad Baraani-Dastjerdi, Hamid Abrishami Moghaddam, Masoomeh Giti, Ali Adjdari Rad, "A New Segmentation Method for Lung HRCT Images," Digital Image Computing: Techniques and Applications, pp. 52, Digital Image Computing: Techniques and Applications (DICTA'05), 2005.
 
 
BibTex
x
 
@article{ 10.1109/DICTA.2005.5,
author = {Rahil Garnavi and Ahmad Baraani-Dastjerdi and Hamid Abrishami Moghaddam and Masoomeh Giti and Ali Adjdari Rad},
title = {A New Segmentation Method for Lung HRCT Images},
journal ={Digital Image Computing: Techniques and Applications},
volume = {0},
year = {2005},
isbn = {0-7695-2467-2},
pages = {52},
doi = {http://doi.ieeecomputersociety.org/10.1109/DICTA.2005.5},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Digital Image Computing: Techniques and Applications
TI - A New Segmentation Method for Lung HRCT Images
SN - 0-7695-2467-2
SP
EP
A1 - Rahil Garnavi,
A1 - Ahmad Baraani-Dastjerdi,
A1 - Hamid Abrishami Moghaddam,
A1 - Masoomeh Giti,
A1 - Ali Adjdari Rad,
PY - 2005
KW - null
VL - 0
JA - Digital Image Computing: Techniques and Applications
ER -
 
Rahil Garnavi, University of Isfahan
Ahmad Baraani-Dastjerdi, University of Isfahan
Hamid Abrishami Moghaddam, K.N.Toosi University of Technology
Masoomeh Giti, Tehran University of Medical Sciences
Ali Adjdari Rad, Amirkabir University of Technology

Image segmentation plays a crucial role in many medical imaging applications by automating or facilitating the delineation of anatomical structures and other regions of interest. The aim of this paper is to develop an accurate and reliable method for segmentation of lung HRCT images using a pixel-based approach.

The proposed method combines traditional concepts, such as global-threshold segmentation, mathematical morphology, edge detection and noise reduction, with new ideas, such as performing geometrical computations to achieve the defined ROIs. Two different approaches are proposed and tested on 100 computed-tomography images. Noise tolerance of the algorithm is calculated considering several parameters and objective criteria. In addition, the image segmentation results were visually validated by radiologists.

Citation:
Rahil Garnavi, Ahmad Baraani-Dastjerdi, Hamid Abrishami Moghaddam, Masoomeh Giti, Ali Adjdari Rad, "A New Segmentation Method for Lung HRCT Images," dicta, pp.52, Digital Image Computing: Techniques and Applications (DICTA'05), 2005
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