DeepNAT-2D

Tensorflow Implementation of 2D version of “Wachinger C, Reuter M, Klein T. DeepNAT: Deep convolutional neural network for segmenting neuroanatomy”

Google-Colab Link

https://colab.research.google.com/drive/1jOd3XYzWK744zV479d4od4fQrddjtjH7?usp=sharing

Research Paper Link

DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy

Presentation Link

https://docs.google.com/presentation/d/1cP-nDOe79ci2ySgskidZrjB0JQo-mHwHrcMaVQJ2Dl4/edit?usp=sharing

How can I run the notebook?

1. Save the complete DeepNAT-2D folder in your google drive.
2. Make a copy of the Colab Notebook and there you go!

References

• Wachinger C, Reuter M, Klein T. DeepNAT: Deep convolutional neural network for segmenting neuroanatomy. Neuroimage. 2018;170:434‐445. doi:10.1016/j.neuroimage.2017.02.035

• The data used was provided for use in the MICCAI 2012 Grand Challenge and Workshop on Multi-Atlas Labeling [B. Landman, S. Warfield, MICCAI 2012 workshop on multi-atlas labeling, in: MICCAI Grand Challenge and Workshop on Multi-Atlas Labeling, CreateSpace Independent Publishing Platform, Nice, France, 2012.]. The data is released under the Creative Commons Attribution-NonCommercial license (CC BY-NC) with no end date. Original MRI scans are from OASIS (https://www.oasis-brains.org/). Labelings were provided by Neuromorphometrics, Inc. (http://Neuromorphometrics.com/) under academic subscription.