DeepVess

DeepVess is a 3D CNN segmentation method with essential pre- and post-processing steps, to fully automate the vascular segmentation of 3D in-vivo MPM images of murine brain vasculature using TensorFlow.

How to use DeepVess

First, see Installing TensorFlow for instructions on how to install TensorFlow.

Second, run prepareImage in MATLAB. (See Help prepareImage)

>> prepareImage()

Third, run DeepVess in Terminal or Python. You can add the address of the output of prepareImage (e.g. ../image3D.h5) as the argument. Otherwise, code will ask you to input it later.

$ python DeepVess.py ../image3D.h5

Finally, run postProcess in MATLAB.

>> postProcess()

Note that prepareImage and postProcess accepts arguments to avoid input request. For more information look at their helps in MATLAB.

>> help prepareImage
>> help postProcess

Publication

• Haft-Javaherian, M; Fang, L.; Muse, V.; Schaffer, C.B.; Nishimura, N.; & Sabuncu, M. R. (2018) Deep convolutional neural networks for segmenting 3D in vivo multiphoton images of vasculature in Alzheimer disease mouse models. arXiv preprint, arXiv:1801.00880.

Contact

• Mohammad Haft-Javaherian mh973@cornell.edu

License

Apache License 2.0