Develop a deep learning model for identifying cell nuclei from histology images. The model should have the ability to generalize across a variety of lighting conditions,cell types, magnifications etc. The generated mask should have the same size as that of the corresponding raw image.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
- Python (used 3.6.6)
- Numpy
- Tensorflow
- Keras
- Skimage
- Scipy
- Sklearn
- Pickle
The data can be downloaded from Kaggle [Dataset]: https://www.kaggle.com/c/data-science-bowl-2018/data
- Run
pip install -r requirements.txt
requirements.txt file can be found in Other Folder - Update the path PATH, TEST_PATH, OUTPUT_PATH in the ipynb
- Run the ipynb notebook
- Output will be saved in the OUTPUT_PATH
- Jupyter Notebook