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TN-SCUI2020-Challenge

This is an example of the Us imaging is used to segment and classify thyroid nodule.

Prerequisities

The following dependencies are needed:

  • numpy >= 1.11.1
  • SimpleITK >=1.0.1
  • tensorflow-gpu ==1.14.0
  • pandas >=0.20.1
  • scikit-learn >= 0.17.1

How to Use

  • 1、when download the all project,check out the segmeatationdata.csv and classifydata.csv,put your train data into same folder.
  • 2、run vnet2d_train.py for vnet2d segmeatation training:make sure train data have effective path
  • 3、run vnet2d_inference.py for vnet2d segmeatation inference:make sure test data have effective path
  • 4、run resnet2d_train.py for resnet2d classify training:make sure train data have effective path
  • 5、run resnet2d_inference.py for resnet2d classify inference:make sure test data have effective path

Result

  • segment train loss and train accuracy

  • classify train loss and train accuracy

  • test dataset segmentation result:left is source image,median is ground truth mask,right is predict mask

  • test dataset leadboard

  • more detail and trained model can follow my WeChat Public article.

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