![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextgreen.png)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextred.png)
![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextgreen.png)
![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltext_open_medium.gif)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextred.png)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltext_restricted_medium.gif)
Detection of Lung Lesions in Lung Cancer Image using HE and Fuzzy C-Means Algorithm
Subscribe/Renew Journal
Lung cancer is one of the leading causes of death in the world. The early detection of cancer can be helpful in curing the disease completely. An early diagnosis of cancer can increase the chance of patient‟s survival from an average of 14% up to 49%. So the requirement of techniques to detect the occurrence of cancer nodule in early stage is increasing. There are different techniques existing but none of those provide better accuracy of detection. This paper provides a Computer Aided Diagnosis System (CAD) for early detection of lung cancer nodules from the Chest Computer Tomography (CT) images. This work represents a computer assisted diagnosis system of lung nodules with the help of two models, the extraction of lung parts can be achieved through the super imposition of input image with the lungs cropped image through Hand free cropping algorithm and then the enhancement of image is achieved by one of the contrast stretching techniques called CLAHE. The statistical values are calculated using MIPAV software.
Keywords
Lung Cancer, Computer Aided Diagnosis, Image Contract, CLAHE, Hand Free Cropping.
User
Subscription
Login to verify subscription
Font Size
Information
![](https://i-scholar.in/public/site/images/abstractview.png)
Abstract Views: 170
![](https://i-scholar.in/public/site/images/pdfview.png)
PDF Views: 2