DocumentCode :
2641954
Title :
Computer aided diagnosis for pulmonary nodules by shape feature extraction
Author :
Takei, Kazunori ; Homma, Noriyasu ; Ishibashi, Tadashi ; Sakai, Masao ; Yoshizawa, Makoto
Author_Institution :
TIS Inc., Tokyo
fYear :
2007
fDate :
17-20 Sept. 2007
Firstpage :
1964
Lastpage :
1967
Abstract :
In this paper, we propose a new diagnosis method of pulmonary nodules in CT images to reduce false positive (FP) rate for high true positive (TP) rate conditions. An essential core of the method is to extract two novel and effective features from the raw CT images: One is orientation features of nodules in a region of interest (ROI) extracted by a gabor filter, while the other is variation of CT values of the ROI in the direction along body axis. By using the extracted features, a principal component analysis technic and neural network approaches are then used to discriminate between nodule and non-nodule images. Simulation results show that discrimination performance using the proposed features is extremely improved compared to that of the conventional method.
Keywords :
Gabor filters; computerised tomography; feature extraction; lung; medical image processing; neural nets; principal component analysis; CT images; Gabor filter; computer aided diagnosis; false positive rate reduction; image discrimination; neural network; orientation features; principal component analysis; pulmonary nodules; region of interest extraction; shape feature extraction; Cancer; Computed tomography; Data mining; Feature extraction; Gabor filters; Lungs; Neural networks; Principal component analysis; Shape; X-ray imaging; Computer aided diagnosis; X-ray CT images; feature extraction; pulmonary nodules;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
SICE, 2007 Annual Conference
Conference_Location :
Takamatsu
Print_ISBN :
978-4-907764-27-2
Electronic_ISBN :
978-4-907764-27-2
Type :
conf
DOI :
10.1109/SICE.2007.4421308
Filename :
4421308
Link To Document :
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