A Study on Lung Cancer Detection in CT Images Using Medical Image processing with Deep Learning Techniques

DOI

10.2991/978-94-6463-250-7_3How to use a DOI?

Keywords

lung cancer; CT images; artificial neural networks; deep learning; convolutional neural network; support vector machines

Abstract

Several medical imaging applications have shown success with deep learning, ushering us further into AI technology. For a single activity, the availability of massive amounts of data with annotations, as well as developments in high-performance computing, are widely credited with AI's success. Medical imaging, on the other hand, poses distinct problems to DL techniques. Deep learning algorithms have recently gained traction as the preferred mode for processing medical images. Because of their efficient learning abilities and ability to deal with complex problems relatively rapidly, these algorithms are appropriate for handling certain image processing issues. Lung cancer is the most diagnosed cancer; many people have been infected, and if the disease is not detected early on, the patient has barely any chance of survival. Artificial intelligence methods for early detection are required for the reasons mentioned above and to help in the fight against this terrible disease. This study gives a brief overview of the various Deep Learning technologies utilized in lung cancer detection and their performance. Rather than providing a full literature review, we discuss published research relevant to these case Scenarios. We'll wrap things up with a recommendations and explanation of some successful potential possibilities. Metrics such as sensitivity, accuracy and specificity will be used to evaluate the effectiveness of this strategy.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - D. E. Mariana Jaincy
AU  - Prasanthi
PY  - 2023
DA  - 2023/10/17
TI  - A Study on Lung Cancer Detection in CT Images Using Medical Image processing with Deep Learning Techniques
BT  - Proceedings of the 6th International Conference on Intelligent Computing (ICIC-6 2023)
PB  - Atlantis Press
SP  - 8
EP  - 14
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-250-7_3
DO  - 10.2991/978-94-6463-250-7_3
ID  - MarianaJaincy2023
ER  -