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AN EFFICIENT MODE DETECTION TECHNIQUE OF PULMONARY NODULE IN LUNG CANCER
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| Author:
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ARUN MATHEWS, M.K. JEYAKUMAR
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| Abstract:
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Lung cancer is a type of cancer that begins in the lungs. Lung cancer is the leading cause of cancer deaths in many
countries, among both men and women. People who smoke have the greatest risk of lung cancer, though lung cancer
can also occur in people who have never smoked. The general prognosis of lung cancer is poor because doctors tend
not to find the disease until it is at an advanced stage. Tumors can be benign or malignant. Benign tumors usually
can be removed and do not spread to other parts of the body. Malignant tumorsenter into the bloodstream or
lymphatic system and then spread to other sites in the body. Therefore it is very important to find the cancer affected
lung region in the earlier stage. By using Linear Iterative Clustering the noise is removed and the color base is
provided. In the segmentation process the cancer affected left bottom area is detected and segmented by using
Adjustable surface normal overlapping and in classification Advanced Grey Wolf Optimization is used. In this research
paper performance output is calculated in the cancer affected area with 100% precision, sensitivity and with best
accuracy.
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| Keyword:
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Improved Simple Linear Iterative Clustering (ISLIC), Histogram equalization, Adjustable surface normal overlap, A-GWO
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| EOI:
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-
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| DOI:
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https://doi.org/10.31838/ijpr/2018.10.04.021
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| Download:
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