LCDctCNN: Lung Cancer Diagnosis of CT scan Images Using CNN Based Model

Muntasir Mamun, Md Ishtyaq Mahmud, Mahabuba Meherin, Ahmed Abdelgawad

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The most deadly and life-threatening disease in the world is lung cancer. Though early diagnosis and accurate treatment are necessary for lowering the lung cancer mortality rate. A computerized tomography (CT) scan-based image is one of the most effective imaging techniques for lung cancer detection using deep learning models. In this article, we proposed a deep learning modelbased Convolutional Neural Network (CNN) framework for the early detection of lung cancer using CT scan images. We also have analyzed other models for instance Inception V3, Xception, and ResNet-50 models to compare with our proposed model. We compared our models with each other considering the metrics of accuracy, Area Under Curve (AUC), recall, and loss. After evaluating the model's performance, we observed that CNN outperformed other models and has been shown to be promising compared to traditional methods. It achieved an accuracy of 92%, AUC of 98.21%, recall of 91.72%, and loss of 0.328.

Original languageEnglish
Title of host publicationProceedings of the 10th International Conference on Signal Processing and Integrated Networks, SPIN 2023
EditorsManoj Kumar Pandey, J. K. Rai, Pradeep Kumar, Ashwani Kumar Dubey, Anil Kumar Shukla
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages205-212
Number of pages8
ISBN (Electronic)9781665490993
DOIs
StatePublished - 2023
Event10th International Conference on Signal Processing and Integrated Networks, SPIN 2023 - Noida, India
Duration: Mar 23 2023Mar 24 2023

Publication series

NameProceedings of the 10th International Conference on Signal Processing and Integrated Networks, SPIN 2023

Conference

Conference10th International Conference on Signal Processing and Integrated Networks, SPIN 2023
Country/TerritoryIndia
CityNoida
Period03/23/2303/24/23

Keywords

  • CNN
  • CT scan imaging
  • Deep Learning
  • Inception V3
  • Lung cancer
  • ResNet-50
  • Xception

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