kristin-zlchen/luna16_multi_size_3dcnn

An implement of paper "Multi-level Contextual 3D CNNs for False Positive Reduction in Pulmonary Nodule Detection"

luna16_multi_size_3dcnn

An implement of paper "Multi-level Contextual 3D CNNs for False Positive Reduction in Pulmonary Nodule Detection"

The detail about the paper can be found luna16 3DCNN

0 required

• numpy

• PIL(or Pillow)

• numpy

• SimpleITK

• pandas

• matplotlib

• Tensorflow >1.3

1 process step

First run data_prepare.py to extract cubic(both real nodule and fake ones) from raw CT files. This may take hours and the output of this step is

• cubic_npy
• cubic_normalization_npy
• cubic_normalization_test

the total size of those file is around 100GB,please leave enough disk.

Then run main.py to train model,inference step will be ran as follow,this step is rather slow cause of huge number of data.