Abstract
Skin-cancer is the most common type of cancer among all other
types of cancers spreading both developed and developing countries. In
this paper, a web service is developed in order to help physicians as
well as individuals to upload an image and diagnose the particular types
of lesions. Computer vision is used to analyse lesions on images by
providing computers with somewhat similarity as humans do. For this a
Convolution Neural Network (CNN) is used with multi classification on
International Skin Imaging Collaboration (ISIC) 2018 dataset with
HAM10000 images. This dataset is a meta-data which has various types of
images with seven different labels. At first, the model is trained with
a larger training set and saved in a zip folder. Secondly, a web service
is created where users or a doctor can upload an image for
classification. Thirdly, the images uploaded are pre-processed as there
is noise, hairs on image. Techniques like resizing, normalisation,
thresholding, black-hat filtering and inpainting are used for this
purpose. After this, the saved model is called to define whether the
uploaded image is benign or malignant. The experimental results reveal
that the proposed model is superior in terms of detection and diagnosis
accuracy as compared to modern methods.
