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Important: make sure your image file formats are supported by IKOSA Portal File formats |
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Important: Non-WSI formats of 2D and multichannel images are supported up to a maximum image size of 625 Megapixel (e.g. 25,000 x 25,000 Pixel). |
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Before you start training your own algorithms, you need to log in to IKOSA https://app.ikosa.ai/auth/login and navigate to the IKOSA AI page.
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Upload images
Annotate images
How-to annotate an image? and How-to draw a ROI?
In addition, we explain how to correctly use annotations and ROI(s) for your algorithm training here: https://kmlvision.atlassian.net/wiki/spaces/KB/pages/3202252814#How-to-draw-ROI-for-algorithm-training-with-IKOSA-AI%3F%5BinlineExtension%5D in a section of our article called How to draw ROI(s) for algorithm training with IKOSA AI? (see in the table of contents)
Basic rules for a successful training
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Important:
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Currently, IKOSA AI covers semantic and instance segmentation tasks only. However, image classification and object detection will also be supported in the near future.
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The extended training option is recommended as a second refinement step and can yield a significant improvement in dice coefficient (depending on the data set) providing you with even better results.
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8. Review your selections and start the training
Review your selections before starting your algorithm training.
Give your training a name and start it!
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Wait until the training is completed
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If you are satisfied with the performance of the algorithm and have thoroughly checked the report, you can deploy your model for further use: How-to deploy and use a trained algorithm?
If you need any help with that, we have prepared an extra section with a couple of how-to articles Interpretation of training results.
Share this information with your team members/colleagues and discuss your next training. Enjoy your algorithm training!
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