Lung Cancer Detection Using GLCM based Micro Vascular Decompression Analysis

Authors

  • ANEETA SINGH Student, Department Of Electrical Engineering,BBSB Engineering College, Fatehgarh Sahib, Punjab-140406 .
  • NAVNEET KAUR Prof, Department, Of Electrical Engineering, BBSB Engineering College, Fatehgarh Sahib, Punjab-140406

Keywords:

Manet Routing, Energy Efficiency, EPAR, Cryptography

Abstract

Image processing techniques are widely used in the medical field for image improvement in earlier detection
and treatment stages. Here, time factor is crucial to discover the abnormality in target images, especially in cancer
tumors such as lung cancer. Lung cancer is a disease characterized by uncontrolled growth of cell in tissues of the lung.
If left untreated, this growth can spread beyond the lungs, even, into other parts of the body. Image quality and accuracy
are the core factors. Image quality assessment and improvement depend on the enhancement stage where a low preprocessing technique is used, which is based on Gabor filter within Gaussian rules. For early detection and treatment
stages image processing technique are widely used and for prediction of lung cancer, identification of genetic as well as
environmental factors are very important in developing novel method of lung cancer prevention. In various cancer
tumours such as lung cancer the time factor is very important to discover the abnormality issue in target images.
Prediction of lung cancer we consider significant pattern and their corresponding weight age and score using decision
tree algorithm. Using the significant pattern tool for lung cancer prediction system will develop

Published

2017-04-25

How to Cite

ANEETA SINGH, & NAVNEET KAUR. (2017). Lung Cancer Detection Using GLCM based Micro Vascular Decompression Analysis. International Journal of Advance Engineering and Research Development (IJAERD), 4(4), 1181–1187. Retrieved from https://ijaerd.com/index.php/IJAERD/article/view/2853