| Issue |
ITM Web Conf.
Volume 32, 2020
International Conference on Automation, Computing and Communication 2020 (ICACC-2020)
|
|
|---|---|---|
| Article Number | 03029 | |
| Number of page(s) | 9 | |
| Section | Computing | |
| DOI | https://doi.org/10.1051/itmconf/20203203029 | |
| Published online | 29 July 2020 | |
Automated Non-invasive Diagnosis of Melanoma Skin Cancer using Dermo-scopic Images
Department of Computer Engineering, Ramrao Adik Institute of Technology, Nerul, Navi Mumbai, 400706, India
* e-mail: huda.gm.khan@gmail.com
Melanoma skin cancer is one of the deadliest cancers today, the rate of which is rising exponentially. If not detected and treated early, it will most likely spread to other parts of the body. To properly detect melanoma, a skin biopsy is required. This is an invasive technique which is why the need for a diagnosis system that can eradicate the skin biopsy method arises. It is observed that the proposed method is successfully detecting and correctly classifying the malignant and non-malignant skin cancer. Finally, a neural network is used to classify benign and malignant images from the extracted features. Keywords: Melanoma, non-invasive, skin lesion, neural network.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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