A Survey on Convolutional Neural Network (Deep-Learning Technique) -Based Lung Cancer Detection

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Lakshmi Narayana Gumma ◽  
R. Thiruvengatanadhan ◽  
LakshmiNadh Kurakula ◽  
T. Sivaprakasam
Author(s):  
Giovanni Da Silva ◽  
Aristófanes Silva ◽  
Anselmo De Paiva ◽  
Marcelo Gattass

Lung cancer presents the highest mortality rate, besides being one of the smallest survival rates after diagnosis. Thereby, early detection is extremely important for the diagnosis and treatment. This paper proposes three different architectures of Convolutional Neural Network (CNN), which is a deep learning technique, for classification of malignancy of lung nodules without computing the morphology and texture features. The methodology was tested onto the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), with the best accuracy of 82.3%, sensitivity of 79.4% and specificity 83.8%.


2020 ◽  
Vol 08 (03) ◽  
pp. 35-42
Author(s):  
Tasnim Ahmed ◽  
Mst. Shahnaj Parvin ◽  
Mohammad Reduanul Haque ◽  
Mohammad Shorif Uddin

Author(s):  
Sheetal P

A risk factor is anything that increases chances of getting a disease, such as cancer. Thus diagnosing the cancer at the earliest stage is very important. Nowadays any cancer affects the human and may lead to death and lung cancer is one of its kind.to decrease the mortality rate and give a good treatment for the affected ones we need a better technique to diagnosis the lung cancer in initial stage itself. Early prediction of Lung Cancer will help with the survival of cancer patients. Machine Learning and Deep Learning have been widely used in the diagnosis of Lung Cancer and on the early detection. The main aim of the research is to review the role of deep learning in Lung Cancer detection and diagnosis. So we have used the convolutional neural network (CNN) which is a class of deep neural network which presents lung cancer detection using Radiology Images.


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