目录

• 安装环境
• 数据处理
• 预处理
• 训练
• 测试

MIC-DKFZ/nnUNet
选择Linux环境运行该项目，Windows环境需要更改较多的参数，暂不支持。

安装环境

可以查看另一篇

数据处理

2D数据转成伪3D数据，即z轴层数为1或3（灰度图为1，彩图为3）。

参考：nnUNet/nnunet/dataset_conversion/Task120_Massachusetts_RoadSegm.py

直接转换数据，将数据存放到nnUNet_raw_data_base/nnUNet_raw_data/Task120_MassRoadsSeg

1. 文件夹目录

   └─Task120_MassRoadsSeg│  dataset.json│  ├─imagesTr│      img-1_0000.nii.gz│      img-1_0001.nii.gz│      img-1_0002.nii.gz│      img-2_0000.nii.gz│      img-2_0001.nii.gz│      img-2_0002.nii.gz│      img-3_0000.nii.gz│      img-3_0001.nii.gz│      img-3_0002.nii.gz│      img-4_0000.nii.gz│      img-4_0001.nii.gz│      img-4_0002.nii.gz│      img-5_0000.nii.gz│      img-5_0001.nii.gz│      img-5_0002.nii.gz│      ...├─imagesTs│      img-10.nii.gz│      img-11.nii.gz│      ...└─labelsTrimg-1.nii.gzimg-2.nii.gzimg-3.nii.gzimg-4.nii.gzimg-5.nii.gz...
   

2. json文件信息

   nnUNet/nnunet/dataset_conversion/utils.py里面的函数generate_dataset_json可以生成相应任务的json文件。

   { 
   "name": "MassRoadsSeg", 
   "description": "MassRoadsSeg",
   "reference": "https://www.kaggle.com/insaff/massachusetts-roads-dataset",
   "licence":'hands off!',
   "release":"1.0 06/08/2018",
   "tensorImageSize": "4D",
   "modality": { "0": "Red","1": "Green","2": "Blue"}, "labels": { "0": "background", "1": "street"}, "numTraining": 804, "numTest": 13,"training":[{"image":"./imagesTr/img-1.nii.gz","label":"./labelsTr/img-1.nii.gz"},{"image":"./imagesTr/img-2.nii.gz","label":"./labelsTr/img-2.nii.gz"},{"image":"./imagesTr/img-3.nii.gz","label":"./labelsTr/img-3.nii.gz"},{"image":"./imagesTr/img-4.nii.gz","label":"./labelsTr/img-4.nii.gz"},{"image":"./imagesTr/img-5.nii.gz","label":"./labelsTr/img-5.nii.gz"},...],"test":["./imagesTs/img-10.nii.gz","./imagesTs/img-11.nii.gz",...]}

预处理

# 只进行2d预处理，不进行3d预处理
nnUNet_plan_and_preprocess -t 120 -pl3d None

训练

nnUNet_train 2d nnUNetTrainerV2 120 0

测试

nnUNet_predict -i /root/nnUNet_raw_data_base/nnUNet_raw_data/Task120_MassRoadsSeg/imagesTs -o /root/nnUNet_trained_models/nnUNet/2d/Task120_MassRoadsSeg/nnUNetTrainerV2__nnUNetPlansv2.1/fold_0/infer -t 120 -m 2d