计算机科学
卷积神经网络
人工智能
模式识别(心理学)
肺癌
深度学习
图像(数学)
分割
特征(语言学)
计算机视觉
作者
Tasnim Ahmed,Mst. Shahnaj Parvin,Mohammad Reduanul Haque,Mohammad Shorif Uddin
标识
DOI:10.4236/jcc.2020.83004
摘要
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.
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