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Minor formatting proposals #16

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19 changes: 10 additions & 9 deletions README.md
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
# 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
> 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 @@ -12,24 +12,24 @@ The following dependencies are needed:
- scikit-learn >= 0.17.1

## How to Use
(re)implemented the model with tensorflow in the paper of "Milletari, F., Navab, N., & Ahmadi, S. A. (2016) V-net: Fully convolutional neural networks for volumetric medical image segmentation.3DV 2016"
(re)implemented the model with tensorflow in the paper of "Milletari, F., Navab, N., & Ahmadi, S. A. (2016) V-net: Fully convolutional neural networks for volumetric medical image segmentation. 3DV 2016"

**1、download trained data,download dataset：https://promise12.grand-challenge.org/download/ ,if you can't download it,i have shared it:https://pan.baidu.com/s/1y9YAAQKdD3OMOMyamx9MdA, password:whbf**
**1. download trained data, download dataset：https://promise12.grand-challenge.org/download/, if you can't download it, I have shared it: https://pan.baidu.com/s/1y9YAAQKdD3OMOMyamx9MdA, password: whbf**

**2、the file of promise12Vnet3dImage.csv,is like this format:
**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\.**
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**
**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.**
**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, password:0nb6**
**5. download trained model: https://pan.baidu.com/s/1B869czIPfIL8wxDKgIednQ, password: 0nb6**

**6、download test data: https://pan.baidu.com/s/1pDCQzTxUmyYdwDinBJKTuA, password:s0jt**
**6. download test data: https://pan.baidu.com/s/1pDCQzTxUmyYdwDinBJKTuA, password: s0jt**

## Result
MICCAI Grand Challenge Result
Expand All @@ -51,6 +51,7 @@ the trained process:0 epoch——GTMask and PredictMask
the predict result
![](mask_15_epoch.png)
![](src_15_epoch.png)

## Contact
* https://github.com/junqiangchen
* email: 1207173174@qq.com
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