README.md~

# DeepLung:

Please add paper into reference if the repository is helpful to you.
Zhu, Wentao, Chaochun Liu, Wei Fan, and Xiaohui Xie. "DeepLung: 3D Deep Convolutional Nets for Automated Pulmonary Nodule Detection and Classification." arXiv preprint arXiv:1709.05538 (2017).

Dependecies: Ubuntu 14.04, python 2.7, CUDA 8.0, cudnn 5.1, h5py (2.6.0), SimpleITK (0.10.0), numpy (1.11.3), nvidia-ml-py (7.352.0), matplotlib (2.0.0), scikit-image (0.12.3), scipy (0.18.1), pyparsing (2.1.4), pytorch (0.1.10+ac9245a) (anaconda is recommended)

Download LUNA16 dataset from https://luna16.grand-challenge.org/data/

Download LIDC-IDRI dataset from https://wiki.cancerimagingarchive.net/display/Public/LIDC-IDRI

For preprocessing, run ./DeepLung/prepare.py. The parameters for prepare.py is in config_training.py. *_data_path is the unzip raw data path for LUNA16. *_preprocess_result_path is the save path for the preprocessing. *_annos_path is the path for annotations. *_segment is the path for LUNA16 segmentation, which can be downloaded from LUNA16 website.

Use run_training.sh to train the detector. After training and test are done, use the ./evaluationScript/frocwrtdetpepchluna16.py to validate the epoch used for test. After that, collect all the 10 folds' prediction, use ./evaluationScript/noduleCADEvaluationLUNA16.py to get the FROC for all 10 folds. You can directly run noduleCADEvaluationLUNA16.py, and get the performance in the paper.

For nodule classification, first clean the data from LIDC-IDRI. Use the ./data/extclsshpinfo.py to extract nodule labels. humanperformance.py is used to get the performance of doctors. 

dimcls.py is used to get the classification based on diameter. nodclsgbt.py is used to get the performance based on GBM, nodule diameter and nodule pixel. pthumanperformance.py is used for patient-level diagnosis performance. kappatest.py is used for kappa value calculation in the paper.

For classification using DPN, use the code in main_nodcls.py. Use the testdet2cls.py to test the trained model. You may revise the code a little bit for different test settings.

Feel free to ask any questions. Wentao Zhu, wentaozhu1991@gmail.com