Lung Nodule Segmentation in CT Images using
Rotation Invariant Local Binary Pattern
L. G Deep, and S. Gupta. ACEEE International Journal of Signal and Image Processing, 4 (1):
4(January 2013)
Abstract
As the lung cancer is the leading cause of cancer
death in the medical field, Computed Tomography (CT) scan
of the thorax is widely applied in diagnoses for identifying
the lung cancer. In this paper, a technique of rotation invariant
with Local Binary Pattern (LBP) for segmentation of various
lung nodules from the Lung CT cancer data sets is used. This
is tested on various lung data sets from teaching files of
Casimage database and National Cancer Institute (NCI) of
National Biomedical Imaging Archive (NBIA). The results
show the segmented nodules with clear boundaries, which is
helpful in diagnosis of lung cancer. Further, the results are
compared with the watershed segmentation method, which
shows that LBP based method yields better segmentation
accuracy.
%0 Journal Article
%1 gdeep2013nodule
%A G Deep, L Kaur
%A Gupta, S
%D 2013
%E Das, Dr. Vinu V
%J ACEEE International Journal of Signal and Image Processing
%K CT Image_Segmentation LBP Lung_Nodules MATITK
%N 1
%P 4
%T Lung Nodule Segmentation in CT Images using
Rotation Invariant Local Binary Pattern
%U http://searchdl.org/public/journals/2013/IJSIP/4/1/9.pdf
%V 4
%X As the lung cancer is the leading cause of cancer
death in the medical field, Computed Tomography (CT) scan
of the thorax is widely applied in diagnoses for identifying
the lung cancer. In this paper, a technique of rotation invariant
with Local Binary Pattern (LBP) for segmentation of various
lung nodules from the Lung CT cancer data sets is used. This
is tested on various lung data sets from teaching files of
Casimage database and National Cancer Institute (NCI) of
National Biomedical Imaging Archive (NBIA). The results
show the segmented nodules with clear boundaries, which is
helpful in diagnosis of lung cancer. Further, the results are
compared with the watershed segmentation method, which
shows that LBP based method yields better segmentation
accuracy.
@article{gdeep2013nodule,
abstract = {As the lung cancer is the leading cause of cancer
death in the medical field, Computed Tomography (CT) scan
of the thorax is widely applied in diagnoses for identifying
the lung cancer. In this paper, a technique of rotation invariant
with Local Binary Pattern (LBP) for segmentation of various
lung nodules from the Lung CT cancer data sets is used. This
is tested on various lung data sets from teaching files of
Casimage database and National Cancer Institute (NCI) of
National Biomedical Imaging Archive (NBIA). The results
show the segmented nodules with clear boundaries, which is
helpful in diagnosis of lung cancer. Further, the results are
compared with the watershed segmentation method, which
shows that LBP based method yields better segmentation
accuracy.},
added-at = {2014-01-17T06:06:31.000+0100},
author = {G Deep, L Kaur and Gupta, S},
biburl = {https://www.bibsonomy.org/bibtex/2c695144dc749485f8cead8c11e51f0ca/ideseditor},
editor = {Das, Dr. Vinu V},
interhash = {5f1b5f681e32c7e838ae769d5c7d18f3},
intrahash = {c695144dc749485f8cead8c11e51f0ca},
journal = {ACEEE International Journal of Signal and Image Processing},
keywords = {CT Image_Segmentation LBP Lung_Nodules MATITK},
month = {January},
number = 1,
pages = 4,
timestamp = {2014-01-17T06:06:31.000+0100},
title = {Lung Nodule Segmentation in CT Images using
Rotation Invariant Local Binary Pattern},
url = {http://searchdl.org/public/journals/2013/IJSIP/4/1/9.pdf},
volume = 4,
year = 2013
}