Melanoma Skin Cancer Classification Using Deep Learning Convolutional Neural Network

Authors

  • S. Mohan Kumar1 , J. Ram Kumar2 , K. Gopalakrishnan3

DOI:

https://doi.org/10.37506/mlu.v20i3.1421

Keywords:

Skin cancer, Computer Aided Diagnosis, Feature Extraction, Convolutional Neural Network

Abstract

In the recent years skin cancer skin cancer is emerging as one of the most complex diseases in which

diagnosis is very challenging. Melanoma is generally characterized by the uncontrolled growth of body

cells which might be caused due to prolonged exposure to UV rays produced by sun. Skin cancer can be

categorized as basal cell carcinoma, squamous cell carcinoma and melanoma among which melanoma is

considered as the most difficult to detect and if detected on time, melanoma is curable. Computer vision

and Image processing toolboxes plays a pivotal portion in the field of medical imaging and diagnosis and

is widely used. This paper focuses on a computer aided tool for skin cancer detection (i.e. melanoma).

Dermoscopic images are used as inputs to the CAD system which is subjected to further image processing

in which segmentation, feature extraction and classification is done to finally to differentiate between normal

and melanoma images.

Author Biography

S. Mohan Kumar1 , J. Ram Kumar2 , K. Gopalakrishnan3

1 Research Scholar, Department of Mechanical Engineering, Indian Institute of Technology, Kanpur, India,

2Professor, Department of Mechanical Engineering, Indian Institute of Technology, Kanpur, India,

3Dean- R&D, New Horizon College of Engineering, Bangalore, India

Published

2020-07-24

How to Cite

S. Mohan Kumar1 , J. Ram Kumar2 , K. Gopalakrishnan3. (2020). Melanoma Skin Cancer Classification Using Deep Learning Convolutional Neural Network. Medico Legal Update, 20(3), 351-355. https://doi.org/10.37506/mlu.v20i3.1421