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peterhessey committed Jul 26, 2022
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -58,7 +58,7 @@ with the InnerEye-Gateway, to run inference on InnerEye-DeepLearning models.

Details can be found [here](docs/deploy_on_aml.md).

![docs/deployment.png](sphinx-docs/source/docs/deployment.png)
![docs/deployment.png](sphinx-docs/source/docs/images/deployment.png)

## Licensing

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2 changes: 1 addition & 1 deletion sphinx-docs/source/docs/deploy_on_aml.md
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# Model Deployment

![deployment.png](deployment.png)
![deployment.png](images/deployment.png)

InnerEye segmentation models using a single DICOM series as input and producing DICOM-RT can be integrated with DICOM networks using:

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2 changes: 1 addition & 1 deletion sphinx-docs/source/docs/innereye_deeplearning.md
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Expand Up @@ -102,7 +102,7 @@ with the InnnEye-Gateway, to run inference on InnerEye-DeepLearning models.

Details can be found [here](deploy_on_aml.md).

![deployment.png](./deployment.png)
![deployment.png](images/deployment.png)

## More information

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2 changes: 1 addition & 1 deletion sphinx-docs/source/docs/model_diagnostics.md
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Expand Up @@ -22,4 +22,4 @@ scan. Dark red indicates voxels that are sampled very often, transparent red ind
infrequently.

Example thumbnail when viewed in the AzureML UI:
![Azure ML patch sampling screenshot](screenshot_azureml_patch_sampling.png)
![Azure ML patch sampling screenshot](images/screenshot_azureml_patch_sampling.png)

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