Abstract
Problem statement: Computer Tomography (CT) has been considered as the most sensitive imaging technique for early detection of lung cancer. Approach: On the other hand, there is a requirement for automated methodology to make use of large amount of data obtained CT images. Computer Aided Diagnosis (CAD) can be used efficiently for early detection of Lung Cancer. Results: The usage of existing CAD system for early detection of lung cancer with the help of CT images has been unsatisfactory because of its low sensitivity and False Positive Rates (FPR). This study presents a CAD system which can automatically detect the lung cancer nodules with reduction in false positive rates. In this study, different image processing techniques are applied initially in order to obtain the lung region from the CT scan chest images. Then the segmentation is carried with the help of Fuzzy Possibility C Mean (FPCM) clustering algorithm. Conclusion/Recommendations: Finally for automatic detection of cancer nodules, Support Vector Machine (SVM) is used which helps in better classification of cancer nodules. The experimentation is conducted for the proposed technique by 1000 CT images collected from the reputed hospital.
Highlights
The Computer Aided Diagnosis (CAD) (Yamamoto et al, 1996; Wiemker et al, 2002) system is very essential for early detection of lung cancer
Yamamoto et al (2000) explained Computer aided diagnosis system with functions to assist comparative reading for lung cancer based on helical Computer Tomography (CT) image
Support Vector Machine (SVM) technique is applied in order to classify the cancer nodules
Summary
This study initially apply the different image processing techniques such as Bit-Plane Slicing, Erosion, Median Filter, Dilation, Outlining, Lung Border Extraction and Flood-Fill algorithms for extraction of lung region. Related work: Yamomoto et al (1996) proposed image processing for computer-aided diagnosis of lung cancer by CT (LSCT). This study presents the image processing method for computer-aided diagnosis of lung cancer by CT (LSCT).
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