wudangbio / cc-cruiser

CC-Cruiser is an intelligence agent involving three functional networks: “identification networks” for screening for CC in populations, “evaluation networks” for risk stratification among CC patients and “strategist networks” to assist in treatment decisions by ophthalmologists.

• Please feel free to contact us for any questions or comments: Erping Long, E-mail: [email protected].
• For auto-cutting, the "cut.m" is the startup file and could be executed in MATLAB. The representative samples before and after auto-cutting is presented.
• All codes for deep-learning convolutional neural networks were executed in the Caffe (Convolutional Architecture for Fast Feature Embedding) framework with Ubuntu 14.04 64bit + CUDA (Compute Unified Device Architecture).
• The /DL-Source code/createdata contains the dataset for one-time training and testing. The training and testing records are saved as test.txt and train.txt. The script "create_imagenet.sh" is used to generate the dataset. The file "make_imagenet_mean.sh" is used to generate the mean file for dataset accordingly.
• The file "train.sh" in /DL-Source code/myself is used for network training.
• The file "test.sh" in /DL-Source code/myself is used for testing.
• The "yunxing_cnn.py" in /DL-Source code/python_script could be used to test and have the evaluation indices.