Hybrid Application Based Skin Lesion Analyzer Using Deep Neural Networks
1S. Poornima, Shivang Kaul, Yash Aggarwal, M. Pushpalatha
Skin cancer with more than 5 million cases reported every year. Early detection can increase the probability of survival. In recent study it was shown neural networks outperform medical board certified doctors in classifying lesions as cancerous. We intend to build a whole system encompassing Image capturing processing it by neural net , sending the response back to the device and formulating a report for the user. We intent to use CNNs to classify the image of skin lesion into 7 categories of cancerous lesions: Melanoma, Benign Keratosis, Actinic Keratoses, Dermatofibroma, Vascular skin lesion and Basal Cell Carcinoma. Our goal is to make the system easily usable by untrained users and make detecting skin cancer easy with higher efficiency.
Neural Networks, Image Processing, Convolu-tional Neural Networks, Skin Cancer Detection, Skin Lesion Imaging, App Development, Localization Algorithms, Cloud Computing, GCP, Compute Engine, App Engine.