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Semantic & syntax issues (proposals) #5

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15 changes: 8 additions & 7 deletions README.md
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# ImageSegmentation With Vnet
> This is an example of the prostate in transversal T2-weighted MR images Segment from MICCAI Grand Challenge:Prostate MR Image Segmentation 2012
> This is an example of the prostate in transversal T2-weighted MR images Segment from MICCAI Grand Challenge: Prostate MR Image Segmentation 2012
![](promise12_header.png)

## Prerequisities
Expand All @@ -13,18 +13,19 @@ The following dependencies are needed:

## How to Use

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

**2、the file of PROMISE2012Image.csv,is like this format:
**2. the file of PROMISE2012Image.csv, is like this format:**
```
D:\Data\PROMISE2012\Augmentation\Image/0_1.bmp
D:\Data\PROMISE2012\Augmentation\Image/0_10.bmp
D:\Data\PROMISE2012\Augmentation\Image/0_2.bmp
......
if you Augmentation 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\.**
```
**if your Augmentation 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 vnet_train_predict.py**
**3. when data is prepared, just run the vnet_train_predict.py**

**4、training the model on the GTX1080,it take 20 hours,and i also attach the trained model in the project,you also just use the vnet_train_predict.py file to predict,and get the segmentation result.**
**4. training the model on the GTX1080, it take 20 hours, and I also attach the trained model in the project, you also just use the vnet_train_predict.py file to predict,and get the segmentation result.**

**5、download trained model:https://pan.baidu.com/s/19E9q6HIUeRB8jpuNhvE2Zg, passworld:obwu**

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