Techniques for Lung Cancer Detection from CT Image
Sugandha Saxena1, S. N. Prasad2, Bhavanishankar3

1Sugandha Saxena, School of ECE, REVA University, Bangalore (Karnataka), India.

2S. N. Prasad, School of ECE, REVA University, Bangalore (Karnataka), India.

3Bhavanishankar, Department of Computer Science and Engineering, RNSIT, Bangalore (Karnataka), India.

Manuscript received on 08 December 2019 | Revised Manuscript received on 16 December 2019 | Manuscript Published on 31 December 2019 | PP: 653-657 | Volume-9 Issue-2S December 2019 | Retrieval Number: B11051292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1105.1292S19

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Abstract: The most lethal disease found in the medical field is lung cancer and early detection of this disease has become a challenge for many doctors and diagnostics. The lung cancer contributes over 15.3% of the total number of new cases diagnosed in the recent years. Smoking and pollution are considered as the major causes of lung cancer. At present, there are huge number of tests available to detect lung cancer such as PET Scan, Computerized Tomography (CT) Scan and X-ray etc. are used to diagnose the disease. By x-ray the picture of the lungs may uncover the unusual mass or nodule. A further developed adaption found in CT scan which can uncover the small lesions in the lung that probably won’t be distinguished with X-ray. Biopsy tests are done for detailed diagnosis of the disease. For accurate and better results, a data mining techniques, machine learning algorithms or deep learning algorithms could be used in the laboratories. In this survey, we have elaborated various existing techniques used so far.

Keywords: Lung Cancer, Data Analytics, Machine Learning Algorithm, Deep Learning Algorithms.
Scope of the Article: Image Security