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Detect-liver-tumor-by-CNN3D-and-UNET3D

1. About this project :

  • It is my graduate thesis in university (2019).
  • Topic: Detect liver tumors in CT image
  • Dataset: Liver tumor Segmentation Challenge (LiTS) contain 131 contrast-enhanced CT images provided by hospital around the world. If you'd like to download it, you can find in this link: https://competitions.codalab.org/competitions/17094
  • Used models: CNN3D and UNet3D (3D mean using convolution 3D (3x3x3), max pooling 3D (3x3x3),...)

2. Requirements about enviroment

  • I use python==3.7.0 and tensorfow==1.14.0.
  • About the library, you can install all packages in requirements.txt by run this command:
pip install -r requirements.txt

3. Analyse dataset

  • Open file: Analyse_data.ipynb

  • Function Histogram() to draw the data's histogram. See below chart: drawing

  • Function Information to log the tumor information (size of tumor in whole image)

  • Function PixelRatio to draw the ratio chart between tumor and back ground. See below chart:

drawing

3. Training and testing

3.1 Training

3.2 Testing

4. Results

5. References