GitHub - ImageGuidedTherapyLab/Segment3DBrainTumorUsingDeepLearningExample

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Name		Name	Last commit message	Last commit date
Latest commit History 135 Commits
nifti		nifti
.gitignore		.gitignore
BraTS2dTest		BraTS2dTest
BraTS2dinMemory		BraTS2dinMemory
BraTs Dataset Train		BraTs Dataset Train
DeepMedic Segment		DeepMedic Segment
DeepMedic-ML		DeepMedic-ML
K-Fold Partition		K-Fold Partition
K-Fold Partition-Softcode		K-Fold Partition-Softcode
README		README
Segment3DBrainTumorUsingDeepLearningExample.m		Segment3DBrainTumorUsingDeepLearningExample.m
TRAININGDATA		TRAININGDATA
applymodel.m		applymodel.m
augment3dPatch.m		augment3dPatch.m
brainTest.json		brainTest.json
brainextractionT1.m		brainextractionT1.m
centerCropMatReader.m		centerCropMatReader.m
createUnet3d.m		createUnet3d.m
densenet_2d.m		densenet_2d.m
densenet_2d_small.m		densenet_2d_small.m
densenet_3d.m		densenet_3d.m
densenet_3d_small.m		densenet_3d_small.m
dicePixelClassification3dLayer.m		dicePixelClassification3dLayer.m
dicePixelClassificationLayer.m		dicePixelClassificationLayer.m
downloadTrained3DUnetSampleData.m		downloadTrained3DUnetSampleData.m
driverroutine.m		driverroutine.m
formalizeunet.m		formalizeunet.m
format2file.m		format2file.m
hccmriunet2d.m		hccmriunet2d.m
hccmriunet3d.m		hccmriunet3d.m
hdenseunet_2d.m		hdenseunet_2d.m
hdenseunet_3d.m		hdenseunet_3d.m
images4d2file		images4d2file
images4d2store.m		images4d2store.m
labels4d2file.m		labels4d2file.m
labels4d2store.m		labels4d2store.m
liverConfig.json		liverConfig.json
livermodel2d.m		livermodel2d.m
makefile		makefile
matRead		matRead
matRead.m		matRead.m
nnWorkspace.mat		nnWorkspace.mat
preprocessBraTSdataset.m		preprocessBraTSdataset.m
unet_2d.m		unet_2d.m
unet_2d_residuals.m		unet_2d_residuals.m
unet_3d.m		unet_3d.m
unet_3d_residuals.m		unet_3d_residuals.m
upsample2dLayer.m		upsample2dLayer.m
upsample3dLayer.m		upsample3dLayer.m

Repository files navigation

Matlab example 
==============

https://www.mathworks.com/help/images/segment-3d-brain-tumor-using-deep-learning.html


Usage
=====

python code is used to setup the kfold fold. 
each fold is configured with a json file to be read by matlab


python setupmodel.py --databaseid=hccmri --initialize
python setupmodel.py --databaseid=hccmri --setuptestset

matlab livermodel.m

matlab livermodel2d.m

matlab code structure
=====================

ImageSegmentationBaseClass.m  - ABC defining the interface
ImageSegmentationDeepMedic.m  - derived class for deep medic architecture
ImageSegmentationDensenet2D.m - derived class for Densenet2D architecture
ImageSegmentationDensenet3D.m - derived class for Densenet3D architecture
ImageSegmentationUnet2D.m     - derived class for Unet2D     architecture
ImageSegmentationUnet3D.m     - derived class for Unet3D     architecture


hccmriunet3d.m - derived class using the 3d unet to segment hcc on mri
hccmriunet2d.m - derived class using the 2d unet to segment hcc on mri