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Download fileCOMPUTER VISION FOR SKIN CANCER DETECTION AND DIAGNOSIS
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posted on 2020-04-07, 09:50 authored by Farah ShahataFarah Shahata, Kamalpreet KaurKamalpreet Kaur, Jinan Fiaidhi— 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 lesion. 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.
History
Email Address of Submitting Author
fshahata@lakeheadu.caSubmitting Author's Institution
Lakeheah UniversitySubmitting Author's Country
- Canada
