Multi-Filtered Image Approach For Detection Of Lung Cancer

DOI

10.2991/978-94-6463-250-7_20How to use a DOI?

Keywords

Texture Frequency; Small Scale Analysis; Non-Linear Filtering and Post Processing

Abstract

This study proposes a cancer detection method using MATLAB. Image pre-processing, feature extraction, and classification are the three steps of the suggested method. On a CT scan of a patient with lung cancer, the suggested approach was evaluated. The proposed method can be further extended to detect other types of cancers by training the machine learning models on appropriate datasets. In conclusion, the proposed method provides an efficient and accurate way of detecting cancer using medical images.

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  - Sajini Sathiaraj
AU  - Prakash Raju
AU  - Murugesan Avudaiappan
AU  - Moorthy Shanmugam
AU  - Prem Narayanan Srinivasan
PY  - 2023
DA  - 2023/10/17
TI  - Multi-Filtered Image Approach For Detection Of Lung Cancer
BT  - Proceedings of the 6th International Conference on Intelligent Computing (ICIC-6 2023)
PB  - Atlantis Press
SP  - 108
EP  - 113
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-250-7_20
DO  - 10.2991/978-94-6463-250-7_20
ID  - Sathiaraj2023
ER  -