Computer Vision News - August 2021

3 Summary 15 InnerEye by Microsoft The checkpoints are chosen from the checkpoints for the epochs specified in the epochs_to_test parameter: the model is evaluated on the validation set for those epochs. The best dice score is written in the checkpoint file (as described in the previous section). In AzureML, there’s a “Models” section where all the source code and checkpoints are saved. The structure is for model: name, a numeric version and tags and properties. Figure 2: InnerEye segmentation models using a single DICOM series as input and producing DICOM-RT can be integrated with DICOM networks using: InnerEye- Gateway: a Windows service that provides DICOM AETs to run InnerEye-DeepLearning models InnerEye-Inference: a REST API for the InnnEye-Gateway to run inference on InnerEye-DeepLearning models. More information for this example can be found on the documentation. Wrapping up! I hope that you discovered something new and interesting this month. Let me know what you are going to do with it! As always, please let me know if you have any questions, or suggestions for the article! It would be great to hear more of you and what tools you would like to be presented; feel free to reach out to me in any of the social media