491506870 / vnet3d

Volume Medical Image Segmentation

ImageSegmentation With Vnet3D

This is an example of the prostate in transversal T2-weighted MR images Segment from MICCAI Grand Challenge:Prostate MR Image Segmentation 2012

How to Use

1、download trained data,download dataset：https://promise12.grand-challenge.org/download/

2、the file of promise12Vnet3dImage.csv,is like this format: D:\Data\PROMISE2012\Vnet3d_data\Vnet3d_patch_train\image/0_10 D:\Data\PROMISE2012\Vnet3d_data\Vnet3d_patch_train\image/0_11 D:\Data\PROMISE2012\Vnet3d_data\Vnet3d_patch_train\image/0_12 ...... if you trained data path is not D:\Data\PROMISE2012,you should change the csv file path just like this:using C:\Data\ replace D:\Data\PROMISE2012.

3、when data is prepared,just run the vnet3d_train_predict.py

4、training the model on the GTX1080,it take 40 hours,and i also attach the trained model in the project,you also just use the vnet3d_train_predict.py file to predict,and get the segmentation result.

5、download trained model:https://pan.baidu.com/s/1B869czIPfIL8wxDKgIednQ, passworld:0nb6

Result

the trained loss result the Vnet3D model the trained process:0 epoch——GTMask and PredictMask 1000 epoch——GTMask and PredictMask 10000 epoch——GTMask and PredictMask the predict result

Contact

• https://github.com/junqiangchen
• email: [email protected]
• WeChat Public number: 最新医学影像技术