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.idea/DeepSintef.iml

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.idea/modules.xml

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README.md

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2.3 Load the plugin into 3DSlicer:
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∘ All Modules > Extension Wizard.
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∘ (Slicer v4.11) Developer Tools > Extension Wizard.
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∘ Select Extension > point to the folder and add it to the path (tick the small box at the bottom).
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∘ Select Extension > point to the folder (second Raidionics) and add it to the path (tick the small box at the bottom).
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A restart of 3DSlicer is necessary after the initial launch with the plugin to have the proper Python environment.
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:warning: old trick necessary for 3DSlicer using Python 2.7
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### 3.2 Setup the Docker images
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• All used Docker images are public, therefore an account is not necessary.
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All images will be automatically downloaded upon model selection.
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All images will be automatically downloaded upon model selection, which might
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take some minutes while the 3DSlicer interface won't be responding.
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## 4. Options
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• A global option should be ticked to check for models update.
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# Extension meta-information
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set(EXTENSION_HOMEPAGE "http://slicer.org/slicerWiki/index.php/Documentation/Nightly/Extensions/Raidionics")
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set(EXTENSION_CATEGORY "AI")
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set(EXTENSION_CONTRIBUTORS ", David (SINTEF)")
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set(EXTENSION_CONTRIBUTORS ", David Bouget (Medical Technology, SINTEF Digital)")
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set(EXTENSION_DESCRIPTION "This is an example of a simple extension")
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set(EXTENSION_ICONURL "http://www.example.com/Slicer/Extensions/Raidionics.png")
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set(EXTENSION_SCREENSHOTURLS "http://www.example.com/Slicer/Extensions/Raidionics/Screenshots/1.png")
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from src.RaidionicsLogic import *
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from src.gui.RaidionicsWidget import *
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"""
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Raidionics is based upon the DeepInfer code (available at https://github.com/DeepInfer/Slicer-DeepInfer)
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"""
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class Raidionics(ScriptedLoadableModule):
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"""Uses ScriptedLoadableModule base class, available at:
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self.parent.title = "Raidionics"
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self.parent.categories = ["Machine Learning"]
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self.parent.dependencies = []
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self.parent.contributors = ["David Bouget (SINTEF)"]
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self.parent.contributors = ["David Bouget (Medical Technology, SINTEF Digital) david.bouget@sintef.no"]
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self.parent.helpText = """
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This is a plugin developped by SINTEF MedTek, allowing users to run pre-trained models on neuro and mediastinum
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data."""
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The Raidionics plugin for 3D Slicer allows users to run pre-trained models for segmentation and standardized
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reporting (RADS) over MRI volumes for patients diagnosed with brain cancer, and CT volumes for patients diagnosed
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with lung cancer.
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The plugin has been developed in the Medical Technology group, Health Research Department, SINTEF Digital.
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"""
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self.parent.helpText += self.getDefaultModuleDocumentationLink()
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self.parent.acknowledgementText = """
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This plugin is based upon the DeepInfer plugin (available at https://github.com/DeepInfer/Slicer-DeepInfer),
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DeepSintef/DeepSintef/src/RaidionicsLogic.py renamed to Raidionics/Raidionics/src/RaidionicsLogic.py

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self.abort = False
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self.dockerPath = SharedResources.getInstance().docker_path
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self.file_extension_docker = '.nii.gz'
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self.logic_task = 'segmentation' # segmentation or diagnosis for now
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self.logic_task = 'segmentation' # segmentation or diagnosis (RADS) for now
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def yieldPythonGIL(self, seconds=0):
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sleep(seconds)
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dataPath = '/home/ubuntu/resources'
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if self.logic_task == 'diagnosis':
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dataPath = '/home/ubuntu/sintef-segmenter/resources'
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# dataPath = '/home/ubuntu/sintef-segmenter/resources'
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dataPath = '/home/ubuntu/Raidionics-segmenter/resources'
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# if widgetPresent:
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# self.cmdStartEvent()

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