SimpleITKSnap is a 3D-image visualization tool. SimpleITKSnap is developed to bridge the gap between 3D-image process programming and its visualization. Comparing to the existing method, SimpleITKSnap have these advantage:

1. Matplotlib-style display: SimpleITKSnap.imshow(yourArray). You don't need to save your processed result to disk, open ITK-SNAP, find the file and load it again.
2. Extension-based design, meet your visualization demand by writing your own extension. The extension development requires minimal code and is super easy to √evelop.

First, clone this repo to your local environment:

git clone https://github.com/JamesQFreeman/simpleITK-Snap.git

Then use pip to install the dependency package:

pip install -r requirements.txt

Then you are ready to go!

You can open 3D image in python code.

import SimpleITKSnap as sis
from SimpleITKSnap.Extension import histogram
array = np.arange(0,256*256*256).reshape(256,256,256)
sis.imshow(array, histogram)

Let's see an example of a brain CT image: To open an image, simply type:

python simpleITK-Snap -f YourFile.nii.gz

You can develop your own extension in two ways:

• Matplotlib-style:

@pltExtension
def yourExtension(array3d:ndarray, x:int, y:int, z:int) -> str:
    plt.whateverYouWant()
    return "Extention display test at {}, {}, {}".format(x,y,z)

• Array-style:

@imgExtension
def yourExtention(array3d:ndarray, x:int, y:int, z:int) -> Tuple[ndarray,str]:
    processed_2d_image = whateverYouWant()
    return processed_2d_image, "Extention display test at {}, {}, {}".format(x,y,z)

SimpleITKSnap is based on:

• python3
• SimpleITK
• numpy
• opencv-python
• PyQt5

Compatibility Test Status:

	Windows 10	OS X	Linux
Build
PyPI

At release 0.1.3, jupyter notebook is supported

• Pypi support

• A doc
• More extension examples

This project is started by JamesQFreeman(wsheng@sjtu.edu.cn) and supported by SJTU MIC lab.