Developing Computer Aided Algorithm for the diagnosis in Dermoscopic images to classify melanoma vs all other types using deep learning approach
Project of ‘Computer Aided Diagnosis’ course ( Master’s Third Semester at University of Girona, January 2020)
The main goal of this project was to design a Computer Aided Diagnosis system to classify dermoscopic images whether any case belongs to Nevus or lesion. System architecture- Image → Normalization → Per instance standardization → Aggressive Data Augmentation → Classification. Steps- 1) Data normalization, 2) Per instance standardization (Standardization by mean and std of the training dataset), 3) Aggressive Data Augmentation (Rotation, Width and Height shift, Zooming, Flipping, Brightness), 4) Classification; Best performing classification model- Ensemble of Inception ResNetv2, Inception v3, EfficientNet B3 (ImageNet-pretrained).