Lung Cancer Detection Using Convolutional Neural Network on Histopathological Images
  IJCTT-book-cover
 		          
 
© 2020 by IJCTT Journal
Volume-68 Issue-10
Year of Publication : 2020
Authors : Bijaya Kumar Hatuwal, Himal Chand Thapa
DOI :  10.14445/22312803/IJCTT-V68I10P104

How to Cite?

Bijaya Kumar Hatuwal, Himal Chand Thapa, "Lung Cancer Detection Using Convolutional Neural Network on Histopathological Images," International Journal of Computer Trends and Technology, vol. 68, no. 10, pp. 21-24, 2020. Crossref, 10.14445/22312803/IJCTT-V68I10P104

Abstract
Lung Cancer is one of the leading life taking cancer worldwide. Early detection and treatment are crucial for patient recovery. Medical professionals use histopathological images of biopsied tissue from potentially infected areas of lungs for diagnosis. Most of the time, the diagnosis regarding the types of lung cancer are error-prone and time-consuming. Convolutional Neural networks can identify and classify lung cancer types with greater accuracy in a shorter period, which is crucial for determining patients` right treatment procedure and their survival rate. Benign tissue, Adenocarcinoma, and squamous cell carcinoma are considered in this research work. The CNN model training and validation accuracy of 96.11 and 97.2 percentage are obtained.

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Keywords
Convolutional Neural Network (CNN), Machine Learning, Lung Cancer, Histopathological Image