Optimal Deep Learning Model to Identify Lung Cancer on CT images

Authors

  • Ankur Chaturvedi, Saurabh Anand

Abstract

Lung cancer is among one of the most parlous and deadly disease in all over the world. Although, prior detection and medication can save life. Computed Tomography (CT) scan images are the best form to diagnosis the cancer which makes difficult for the doctors to explicate and detect the cancer from CT scan images. The main motive behind this research is to compare the various computer-aided techniques and analyze current best technique with their limitation and drawbacks and finally give the new improved model. The method used in the lung cancer detection till now has low accuracy so a new model will be given to attain higher accuracy rate by modifying the methods which are currently used and removing the limitations and drawbacks. Our model is valid for a large number of lung nodules which increases the variation in data and analysis and detection more challenging.

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Published

2020-11-30

How to Cite

Ankur Chaturvedi, Saurabh Anand. (2020). Optimal Deep Learning Model to Identify Lung Cancer on CT images. PalArch’s Journal of Archaeology of Egypt / Egyptology, 17(9), 8061 - 8067. Retrieved from https://archives.palarch.nl/index.php/jae/article/view/5709