Acta Scientific Computer Sciences

Research Article Volume 4 Issue 9

Lung Cancer Detection Using Convolutional Neural Network

Yusuf Musa Malgwi, Ibraim Goni* and Bamanga Mahmud Ahmad

Department of Computer Science, Faculty of Physical Science, Modibbo Adama University, Yola, Nigeria

*Corresponding Author: Ibraim Goni, Department of Computer Science, Faculty of Physical Science, Modibbo Adama University, Yola, Nigeria.

Received: July 08, 2022; Published: August 04, 2022


Lung cancer is one of the deadly diseases in recent years. However, research proved that detection in an early stage improved the chances of survival. The disease is identified using nodules attached to lung walls and lung parenchyma. Nodules on the lungs are the major sign and symptoms for identifying lung cancer. The aim of this research work was to detect lung cancer using convolutional neural network. CT scanned images were obtained and form the datasets for training and testing the models then nodules are classified as benign or malign. The model helps in improving accuracy in identifying nodules in the lungs. Different classifiers such as Multilayered Perceptron and CNN classifiers are used in comparative analysis. Based on these findings it was conclude that the approach of feature extraction with CNN decreases the false positive rate significantly compared to the existing classification methods.

Keywords: Lung Nodules; CNN; Lung Cancer; Multilayered Perceptron


  1. Qi Dou., et al. “Multilevel Contextual 3-D CNNs for False Positive Reduction in Pulmonary Nodule Detection”. IEEE Transactions on Biomedical Engineering7 (2017).
  2. Nouf Alajmi. “Application of Pattern Recognition”. January (2021).
  3. Abdillah B., et al. “Image processing based detection of lung cancer on CT scan images”. In Journal of Physics: Conference Series 893.1 (2017): 012063.
  4. Chauhan D and Jaiswal V. “An efficient data mining classification approach for detecting lung cancer disease”. In 2016 International Conference on Communication and Electronics Systems (ICCES) (2016): 1-8.
  5. Nasser I M andAbu-Naser S S. “Lung Cancer Detection Using Artificial Neural Network”. International Journal of Engineering and Information Systems (IJEAIS)3 (2019): 17-23.
  6. Sharif MI., et al. “A comprehensive review on multi-organs tumor detection based on machine learning”. Pattern Recognition Letters 131 (2020): 30-37.
  7. Alakwaa W., et al. “Lung cancer detection and classification with 3D convolutional neural network (3D-CNN)”. Lung Cancer8 (2017): 409.
  8. Shakeel P M., et al. “Lung cancer detection from CT image using improved profuse clustering and deep learning instantaneously trained neural networks”. Measurement 145 (2019): 702-712.
  9. Bhatia S., et al. “Lung cancer detection: A deep learning approach”. In Soft Computing for Problem Solving (2019): 699-705.
  10. Zeebaree DQ., et al. “Multi-Level Fusion in Ultrasound for Cancer Detection Based on Uniform LBP Features”. (2021).


Citation: Ibraim Goni., et al. “Lung Cancer Detection Using Convolutional Neural Network". Acta Scientific Computer Sciences 4.9 (2022): 06-08.


Copyright: © 2022 Ibraim Goni., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Acceptance rate35%
Acceptance to publication20-30 days

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