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Extraction of Nuclear Region from Sputum Images through Pixel Classification for Early Lung Cancer Detection
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 72 - Number 22 |
| Year of Publication: 2013 |
| Authors: Vineet Kumar, Hitesh Sharma |
10.5120/12675-9373
|
Vineet Kumar, Hitesh Sharma . Extraction of Nuclear Region from Sputum Images through Pixel Classification for Early Lung Cancer Detection. International Journal of Computer Applications. 72, 22 ( June 2013), 35-39. DOI=10.5120/12675-9373
Abstract
In today's world a very vast study has been made in the field of oncology. Now days, Lung Cancer constitutes the major portion of all deaths that occur due to cancer. This deadly disease Cancer is staged according to its severity and also up to where it has spread. It has been said by many doctors and researchers that a survival rate of five years can be increased if lung cancer is diagnosed in the early stages. There are many techniques available to diagnose the cancer. Two of them are Sputum cytology and Fine Needle Aspiration Cytology (FNAC). In these techniques, the presence of cancer cells in the cytological samples is examined. After that Normal cells are differentiated from Cancer cells on the basis of cell and nucleus appearance. In case of images a count of the number of pixels in nucleus, cytoplasm and background region can be made. In this paper the work on extraction of nucleus region from cytological sample images of sputum is presented. The reason is that, nucleus contains deoxyribonucleic (DNA), and DNA is responsible for cell formation and deformation. Threshold is used as a preprocessing step and problem of segmentation is viewed as a three class pixel classification problem. The classification technique used is Bayesian Classification.
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