Detection of Lung Cancer Using Deep Learning

Authors

  • Y. Nagateja B.E. Student, Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bangalore, India
  • G. Renukesh B.E. Student, Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bangalore, India
  • L. Suhas Gowda B.E. Student, Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bangalore, India
  • K. M. Shreyas B.E. Student, Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bangalore, India
  • J. T. Thirurkrihshna Associate Professor, Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bangalore, India

Keywords:

lung nodules, deep learning, CNN, computed tomography, deep neural network

Abstract

In recent years, many computer-aided diagnostic (CAD) systems have been developed to diagnose various diseases. Early detection of lung cancer is becoming increasingly important, made possible through image processing and deep learning technologies. Nodule detectors and feature-based classifiers make up the majority of CAD systems. Computed tomography can help doctors detect lung cancer early. In many cases, the diagnosis of lung cancer is based on the doctor's experience, which can lead to: some patients being overlooked and causing issues. In several fields of medical imaging diagnostics, deep learning has shown to be a popular and effective strategy. Two types of deep neural networks are used to classify lung cancer, such as CNN and DNN.

Downloads

Download data is not yet available.

Downloads

Published

01-05-2022

How to Cite

[1]
Y. Nagateja, G. Renukesh, L. S. Gowda, K. M. Shreyas, and J. T. Thirurkrihshna, “Detection of Lung Cancer Using Deep Learning”, IJRESM, vol. 5, no. 4, pp. 166–168, May 2022.

Issue

Section

Articles