Title
Classification of lung area using multidetector-row CT images
Abstract
Recently, we can get high quality images in the short time for the progress of X-ray CT scanner, and the three dimensional (3-D) analysis of pulmonary organs using multidetector-row CT (MDCT) images, is expected. This paper presents a method for classifying lung area into each lobe using pulmonary MDCT images of the whole lung area. It is possible to recognize the position of nodule by classifying lung area into these lobes. The structure of lungs differs on the right one and left one. The right lung is divided into three domains by major fissure and minor fissure. The left lung is divided into two domains by major fissure. Watching MDCT images carefully, we find that the surroundings of fissures have few blood vessels. Therefore, lung area is classified by extraction of the domain that the distance from pulmonary blood vessels is large and connective search of these extracted domains. These extraction and search are realized by 3-D weighted Hough transform.
Year
DOI
Venue
2002
10.1117/12.467089
Proceedings of SPIE
Keywords
Field
DocType
3-D weighted Hough transform,3-D distance transform,multidetector-row CT,pulmonary organs analysis method,classification of lung area
Nuclear medicine,Hough transforms,Lung,Lobe,Hough transform,Major fissure,Computed tomography,Radiology,Fissure,Medicine
Conference
Volume
ISSN
Citations 
4684
0277-786X
1
PageRank 
References 
Authors
0.48
0
8
Name
Order
Citations
PageRank
t mukaibo110.48
Yoshiki Kawata219254.44
Noboru Niki318866.10
Hironobu Ohmatsu413845.23
Ryutaro Kakinuma59724.90
Kenji Eguchi612942.78
Masahiro Kaneko75519.24
Noriyuki Moriyama814850.47