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lung_nodule_classifier

lung nodule classifier for 9 attribute

Prerequisites

python 3.5.2
pytorch 0.2.0

lidc 9 attribute

  • malignancy (range: 1~5)
  • sphericity (range: 1~5)
  • margin (range: 1~5)
  • spiculation (range: 1~5)
  • texture (range: 1~5)
  • calcification (range: 1~6)
  • internal structure (range: 1~4)
  • lobulation (range: 1~5)
  • subtlety (range: 1~5)

Result

MAE under 0.1 MAE under 0.2 MAE under 0.3 MAE under 0.4 MAE under 0.5 MAE under 0.6 MAE under 0.7 MAE under 0.8 MAE under 0.9 MAE under 1
malignancy 15.24% 24.76% 42.86% 60.00% 71.43% 80.95% 86.67% 92.38% 93.33% 94.29%
sphericity 17.14% 29.52% 50.48% 60.00% 67.62% 72.38% 80.95% 84.76% 89.52% 92.38%
margin 19.05% 38.10% 48.57% 60.95% 67.62% 77.14% 82.86% 85.71% 86.67% 89.52%
spiculation 21.90% 37.14% 63.81% 72.38% 76.19% 81.90% 83.81% 87.62% 88.57% 91.43%
texture 22.86% 59.05% 76.19% 80.95% 84.76% 84.76% 86.67% 89.52% 91.43% 92.38%
calcification 89.52% 89.52% 92.38% 93.33% 93.33% 93.33% 97.14% 99.05% 99.05% 100.00%
internal_structure 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00%
lobulation 19.05% 31.43% 52.38% 67.62% 75.24% 79.05% 85.71% 87.62% 91.43% 92.38%
subtlety 15.24% 32.38% 50.48% 57.14% 67.62% 71.43% 80.95% 86.67% 86.67% 88.57%

Data Download

Training

  • set luna and lidc path: set config_training.py
  • export path: source export_path.sh
  • train, val idx npy make: python preprocess/make_validate_npy.py
  • preprocess data make: python preprocess/prepare.py
  • train: sh train.sh

Reference Code

https://github.com/lfz/DSB2017
https://github.com/juliandewit/kaggle_ndsb2017

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