Deep Learning Methods for Lung Cancer Nodule Classification: A Survey

Authors

  • Pavan Kumar Illa Department of Computer Science and Engineering, SRM Institute of Science and Technology, India and Department of Information Technology, VNRVJIET, Hyderabad, India https://orcid.org/0000-0002-2743-0962
  • T. Senthil Kumar Department of Computer Science and Engineering, SRM Institute of Science and Technology, India
  • F. Syed Anwar Hussainy Department of Computer Science and Engineering, SRM Institute of Science and Technology, India

DOI:

https://doi.org/10.13052/jmm1550-4646.18213

Abstract

Lung cancer is one of the leading causes of cancer related deaths. It is due to the complexity of early detection of nodules. In clinical practice, radiologists find it difficult to determine whether a condition is normal or abnormal by manually analysing CT scan or X-ray images for nodule identification. Currently, various deep learning techniques have been developed to identify lung nodules as benign or malignant, but each technique has its own advantages and drawbacks. This work presents a thorough analysis based on segmentation techniques, Related features-based detection, multi-step detection, automatic detection, and deep convolutional neural network techniques. Performance comparison was conducted on a selected works based on performance measures. A potential research direction for the recognition of lung nodules is given at the end of this study.

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Author Biographies

Pavan Kumar Illa, Department of Computer Science and Engineering, SRM Institute of Science and Technology, India and Department of Information Technology, VNRVJIET, Hyderabad, India

Pavan Kumar Illa Completed his master’s degree in Computer Science & Engineering. From K L University. He is Currently associated with Department of Computer Science & Engineering, SRMIST, Chennai as a Doctoral student and working as Assistant Professor in VNRVJIET, Hyderabad. His research interests include Machine Learning and Deep learning. He has 9 years of teaching & research experience.

T. Senthil Kumar, Department of Computer Science and Engineering, SRM Institute of Science and Technology, India

T. Senthil Kumar Completed Ph.D. in the field of wireless communication, under the guidance of Dr.S. Prabhakaran, Professor, Department of Computer Science & Engineering, SRMIST, Chennai. He is currently working as Assistant Professor (Senior Grade) in SRMIST, Chennai. He has contributed many scientific research papers. His research interests include wireless communication, Machine Learning and Deep learning.

F. Syed Anwar Hussainy, Department of Computer Science and Engineering, SRM Institute of Science and Technology, India

F. Syed Anwar Hussainy, Completed his master’s in information technology. He is Currently associated with SRMIST, Chennai as a Doctoral student. His research interests include Machine Learning and Deep learning

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Published

2021-11-16

Issue

Section

Enabling AI Technologies Towards Multimedia Data Analytics for Smart Healthcare