A Review on Skin Cancer Detection and Classification using Infrared images

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2022 by IJETT Journal
Volume-70 Issue-4
Year of Publication : 2022
Authors : Akila Victor, Bhuvanjeet Singh Gandhi, Muhammad Rukunuddin Ghalib, Asha Jerlin M
  10.14445/22315381/IJETT-V70I4P235

MLA 

MLA Style: Akila Victor, et al. "A Review on Skin Cancer Detection and Classification using Infrared images." International Journal of Engineering Trends and Technology, vol. 70, no. 4, Apr. 2022, pp. 403-417. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I4P235

APA Style: Akila Victor, Bhuvanjeet Singh Gandhi, Muhammad Rukunuddin Ghalib, Asha Jerlin M.(2022). A Review on Skin Cancer Detection and Classification using Infrared images. International Journal of Engineering Trends and Technology, 70(4), 403-417. https://doi.org/10.14445/22315381/IJETT-V70I4P235

Abstract
Skin cancer is considered one of the most complex forms of cancer. If the skin cancer is not treated early, there is a high possibility that cancer could spread to different parts of the body. Melanoma skin cancer count has been increasing day by day. Early detection plays a very vital role in the treatment of cancer. However, present-day technological developments can detect skin cancer as early as possible. This review focuses on the characteristic features such as texture, shape, color, and structure, the essential paradigm for detecting skin cancer. In medical image processing, skin cancer detection at its initial stage can be done through computer-aided detection, artificial intelligence, swarm technique, etc. In the case of an automatic diagnosis system, there are, most importantly, two major steps, namely skin anomaly detection, and classification. We present a thorough review of skin cancer detection and classification using infrared imaging, artificial neural networks, Gaussian classifiers, etc. This review also delivers obligatory information on numerous techniques and primary steps for the automatic detection and classification of skin cancer.

Keywords
Artificial intelligence, Classification, Computer-aided detection, Infrared imaging, Melanoma skin cancer

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