DocumentCode :
1740866
Title :
Automatic segmentation of lung regions in chest radiographs: a model guided approach
Author :
Luo, Hui ; Gaborski, R. ; Acharya, R.
Author_Institution :
Dept. of Comput. Sci. & Eng., State Univ. of New York, Buffalo, NY, USA
Volume :
2
fYear :
2000
fDate :
10-13 Sept. 2000
Firstpage :
483
Abstract :
In this paper, a knowledge-based, fully automatic method for identifying lung regions in digital chest radiographs is described. The method uses an object-oriented knowledge model to appropriately integrate the anatomical knowledge and image processing routines in lung detection. A series of chest radiographs are employed to test the proposed method; the experimental results are encouraging.
Keywords :
diagnostic radiography; image recognition; image segmentation; knowledge based systems; lung; medical image processing; object-oriented methods; anatomical knowledge; automatic segmentation; chest radiographs; digital chest radiographs; image processing routines; knowledge-based fully automatic method; lung regions; model guided approach; object-oriented knowledge model; Anatomy; Deformable models; Diagnostic radiography; Histograms; Image processing; Image segmentation; Lungs; Object oriented modeling; Pixel; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location :
Vancouver, BC, Canada
ISSN :
1522-4880
Print_ISBN :
0-7803-6297-7
Type :
conf
DOI :
10.1109/ICIP.2000.899459
Filename :
899459
Link To Document :
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