Deep Gray Matter (DGM) Segmentation using 3D Convolutional Neural Network: application to QSM

This work is based on:

• Jose Dolz, Christian Desrosiers, Ismail Ben Ayed, 3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study, In NeuroImage, 2017
• joseabernal's solution for iSeg2017. Github

Current outcome

The work has been submitted to ISMRM Workshop on Machine Learning 2018

Some preliminary reports can be found at Medium (Part 1) (Part 2)

Highlight

• Update 2018-02-04:

Larger kernel size (7, 7, 3), add Batch Normalization and auxiliary feature input of spatial coordinates information.

How to use it

1. Put QSM images in datasets/QSM/
2. Put spatial coordinates maps in datasets/X/, datasets/Y/, datasets/Z/
3. Put segmented ROI labels in datasets/label/
4. Run segDGM_3DCNN.ipynb