Skin Cancer Detection using custom CNN (Shallow CNN) in Tensorflow
To build a CNN based model which can accurately detect melanoma. Melanoma is a type of cancer that can be deadly if not detected early. It accounts for 75% of skin cancer deaths. A solution that can evaluate images and alert dermatologists about the presence of melanoma has the potential to reduce a lot of manual effort needed in diagnosis.
- Real world data is expected to have class imbalance issues i.e. some classes with very small sample sizes.
- This can be a challenge in training high performance models (Accuracy and Generalization wise)
- Using appropriate data augmentation techniques it is possible to improve the model performance.
- Python 3.8.13
- Tensoflow 2.9.1
- Kera 2.9.0
- Augmentor 0.2.10
- Numpy 1.23.1
- Pandas 1.4.2
- NVIDIA Driver 515.48.07 (GTX 1070)
- CUDA 11.7
- The dataset consists of 2357 images of malignant and benign oncological diseases, which were formed from the International Skin Imaging Collaboration (ISIC)
Created by [@jaskirat8] - feel free to contact me!