Requirements that should be met to produce optimal results.

Same acquisition mode

Images are acquired in the same acquisition mode for both training and segmentation (e.g. both times with reflection mode, not training with reflected image and segmentation with transmitted image).

Size of objects/representative region

• Objects or representative regions should be of similar pixel size across training and segmentation images.
• For optimal results, object sizes should be no larger than 320*320 pixels.

Image size

• For optimal performance, we recommend keeping the image sizes homogeneous during training, as the smallest image axis across all training images determines the area that the trained model "sees". This ensures that valuable image context is not excluded, which can affect the accuracy of the segmentation. However, if all training images are above 1024*1024 pixels, this recommendation does not apply.
• For segmentation and continuing training, we recommend using images with a minimum size of 1024*1024 pixels, or the size of the smallest image axis across all training images used in the first training, whichever is smaller. This minimum size threshold ensures that the trained model can effectively capture the necessary features in the image, leading to better segmentation results.

Have questions? We're here to help.

Have a question about dataset requirements? Feel free to reach out to our support team.