deveshsangwan / Skin-lesions-classification

This repo includes classifier trained to distinct 7 type of skin lesions

Skin-lesions-classification

This repo includes classifier trained to distinct 7 type of skin lesions.

Dataset

Dataset consists of 10015 images which describe 7 type of lesions. Dataset includes images of following 7 skin lesions:

• Actinic keratoses and intraepithelial carcinoma / Bowen's disease (akiec)
• basal cell carcinoma (bcc)
• benign keratosis-like lesions (solar lentigines / seborrheic keratoses and lichen-planus like keratoses, bkl)
• dermatofibroma (df)
• melanoma (mel)
• melanocytic nevi (nv)
• vascular lesions (angiomas, angiokeratomas, pyogenic granulomas and hemorrhage, vasc)

Dataset link

Model Training

The following CNN models are used:

• InceptionV3
• Resnet152
• VGG19
• Xception
• Ensemble

Results

Model	Accuracy
InceptionV3	0.862
Resnet152	0.802
VGG19	0.835
Xception	0.862
Ensemble	0.875

Conclusion

Out of all the algorithms used, Ensemble of Xception, Resnet152, InceptionV3 gives the best accuracy of 0.8753.