Author(s)

Tasnim Ahmed^1*, Mst. Shahnaj Parvin², Mohammad Reduanul Haque³, Mohammad Shorif Uddin¹

¹Department of Computer Science and Engineering, Jahangirnagar University, Dhaka, Bangladesh.
²Department of Computer Science and Engineering, Central Women’s University, Dhaka, Bangladesh.
³Department of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh.

Early detection of lung nodule is of great importance for the successful diagnosis and treatment of lung cancer. Many researchers have tried with diverse methods, such as thresholding, computer-aided diagnosis system, pattern recognition technique, backpropagation algorithm, etc. Recently, convolutional neural network (CNN) finds promising applications in many areas. In this research, we investigated 3D CNN to detect early lung cancer using LUNA 16 dataset. At first, we preprocessed raw image using thresholding technique. Then we used Vanilla 3D CNN classifier to determine whether the image is cancerous or non-cancerous. The experimental results show that the proposed method can achieve a detection accuracy of about 80% and it is a satisfactory performance compared to the existing technique.

Lung Cancer, Convolutional Neural Network, Tensorflow, CT Scan

Ahmed, T. , Parvin, M. , Haque, M. and Uddin, M. (2020) Lung Cancer Detection Using CT Image Based on 3D Convolutional Neural Network. Journal of Computer and Communications, 8, 35-42. doi: 10.4236/jcc.2020.83004.