DocumentCode :
2716997
Title :
Lung Nodule Diagnosis from CT Images Using Fuzzy Logic
Author :
Samuel, C. Clifford ; Saravanan, V. ; Devi, M. R Vimala
Author_Institution :
VIT Univ., Vellore
Volume :
3
fYear :
2007
fDate :
13-15 Dec. 2007
Firstpage :
159
Lastpage :
163
Abstract :
In this paper we present a technique for recognizing the lung nodules for different diagnosis of lung cancer based on CT images. Nodule detection is carried in the following steps: preprocessing using wavelet technique, biorthogonal wavelet is used for image enhancement. The enhanced image is subjected to Bi-Histogram equalization. The resultant image is more accurate and sharp. The enhanced image is binarised using the thresholding. Then the binarised image is subjected to Morphological transform. The filtered image is segmented and features are extracted. The extracted features are given to the fuzzy inference systems (FIS). The fuzzy system finds the severity of the lung nodules based on the IF-THEN rules.
Keywords :
computerised tomography; fuzzy logic; fuzzy reasoning; image enhancement; medical image processing; wavelet transforms; CT images; bihistogram equalization; biorthogonal wavelet; features extraction; fuzzy inference systems; fuzzy logic; image enhancement; lung cancer; lung nodule diagnosis; morphological transform; nodule detection; wavelet technique; Cancer detection; Computed tomography; Fuzzy logic; Fuzzy systems; Image enhancement; Image reconstruction; Image segmentation; Lungs; Morphology; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Conference on Computational Intelligence and Multimedia Applications, 2007. International Conference on
Conference_Location :
Sivakasi, Tamil Nadu
Print_ISBN :
0-7695-3050-8
Type :
conf
DOI :
10.1109/ICCIMA.2007.236
Filename :
4426360
Link To Document :
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