KiTS19——2019 Kidney Tumor Segmentation Challenge

This is an example of the CT images Kidney Tumor Segmentation

Prerequisities

The following dependencies are needed:

• numpy >= 1.11.1
• SimpleITK >=1.0.1
• opencv-python >=3.3.0
• tensorflow-gpu ==1.8.0
• pandas >=0.20.1
• scikit-learn >= 0.17.1
• json >=2.0.9

How to Use

1、Preprocess

• analyze the ct image,and get the slice thickness and window width and position:run the dataAnaly.py
• keep Kidney region range image:run the data2dprepare.py
• generate patch(128,128,32) kidney image and mask:run the data3dprepare.py
• save patch image and mask into csv file: run the utils.py,like file trainSegmentation.csv
• split trainSegmentation.csv into training set and test set:run subset.py
• generate tumor image and mask:run the tumordata2dprepare.py
• save tumor image and mask path into csv file: run the utils.py,like file traintumorSegmentation.csv
• split traintumorSegmentation.csv into training set and test set

2、Kidney Segmentation

• the VNet model

• train and predict in the script of vnet3d_train.py and vnet3d_predict.py

3、Kidney Tumor Segmentation

• the VNet2d model

• train and predict in the script of vnet2d_tumor_train.py and vnet2d_tumor_predict.py

Result

1、Kidney Segmentation

• the train loss

• 200-209case dice value and result

2、Kidney Tumor Segmentation

Contact

• https://github.com/junqiangchen
• email: 1207173174@qq.com，yixuanwang@hust.edu.cn,1259389904@qq.com
• Contact: junqiangChen，yixuanWang（王艺璇）,junMa(马骏)
• WeChat Number: 1207173174
• WeChat Public number: 最新医学影像技术