Abstract:
Skin cancer is uncontrolled growth of strange skin cells .It occurs
when unrepaired DNA damages to skin cells triggers mutations, or
genetic defects, that lead the skin cells to multiply readily and form
malignant tumors. Image processing is a commonly used method
for skin cancer detection from the appearance of affected area on
the skin. Artificial Neural Network (ANN) is one of the important
branches of Artificial Intelligence, which has been accepted as a brand
new technology in computer science for image processing. Neural
Networks are currently the area of interest in medicine, particularly
in the fields of radiology, urology, cardiology, oncology, etc. Neural
Network plays a vital role in an exceedingly call network. It has been
used to analyse Melanoma parameters Like Asymmetry, Border,
Colour, Diameter, (ABCD), etc. which are calculated using MATLAB
from skin cancer images intending to developing diagnostic
algorithms that might improve triage practices in the emergency
department. Using the ABCD rules for the melanoma skin cancer, we
use ANN in classification stage with Back Propagation Algorithm. Initially,
we train the network with known target values. The network is well
trained with 94.9% accuracy, and then the unknown values are tested
for the cancer classification. This classification method proves to be
more efficient for the skin cancer classification.
