Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)

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Diagnosis of Melanoma Using Thermography: A Review

Authors
Nazneen Akhter1, *, Ramesh Manza2, Sana Shaikh3, Bharti Gawali2, Pravin Yannawar2, Shazia Shaikh1
1Maulana Azad College of Arts, Science and Commerce, Aurangabad, India
2Babasaheb Ambedkar Marathwada University, Aurangabad, India
3Rafiq Zakaria Centre for Higher Learning and Advanced Research, Aurangabad, India
*Corresponding author. Email: getnazneen@gmail.com
Corresponding Author
Nazneen Akhter
Available Online 1 May 2023.
DOI
10.2991/978-94-6463-136-4_40How to use a DOI?
Keywords
Thermography; Thermal imaging; Skin cancer; Melanoma detection; Non-invasive diagnosis of melanoma; Dynamic thermal imaging
Abstract

Cases of skin cancer have become very common in many parts of the world due to modernization in all aspects of life along with many other contributing factors. So it becomes important to study and evolve better and more efficient techniques for the early detection of cancer for faster and higher chances of recovery. Of the three types of skin cancers, melanoma is the deadliest and is characterized by changes in the colour, size or shape of a mole. The major focus lies in studying the evolving melanoma diagnostic techniques that are non-invasive and cause lesser discomfort to the patient. Various emerging technologies are enhancing the diagnostic approaches for melanoma detection out of which one promising technology is thermography. Currently, the assessment of thermography’s effectiveness is in the research phase and studies are still being reported to substantiate its accuracy in the diagnosis of melanoma. This review analyzes the thermal imaging-based experimental studies conducted for melanoma detection with respect to factors like the experimental set-up, performance rates of the approaches, their limitations, and future scope.

Copyright
© 2023 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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Volume Title
Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
Series
Advances in Computer Science Research
Publication Date
1 May 2023
ISBN
978-94-6463-136-4
ISSN
2352-538X
DOI
10.2991/978-94-6463-136-4_40How to use a DOI?
Copyright
© 2023 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.

Cite this article

risenwbib
TY  - CONF
AU  - Nazneen Akhter
AU  - Ramesh Manza
AU  - Sana Shaikh
AU  - Bharti Gawali
AU  - Pravin Yannawar
AU  - Shazia Shaikh
PY  - 2023
DA  - 2023/05/01
TI  - Diagnosis of Melanoma Using Thermography: A Review
BT  - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
PB  - Atlantis Press
SP  - 466
EP  - 473
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-136-4_40
DO  - 10.2991/978-94-6463-136-4_40
ID  - Akhter2023
ER  -