Image List Page
In Image List Page, user could view the thumbnail images in the projects together with meta information. After dividing WSIs into smaller image tiles, the user uploads them into QA in Image List Page.
The user follows instructions in order shown on the Image List Page
Images tiles are sub-divided into 256 x 256 amenable to deep learning. The user can decide whether they want to remove white backgrounds when dividing these image tiles. This function is useful when there are large areas of white backgrounds. ("E.g. TMA spot")
A u-net consisting of a block depth of 5 layers and 113,306 parameters was trained on these patches in an auto-encoding fashion, such that model weights were optimized to reproduce the input as output with high fidelity. This helped create an initialized base model that was subsequently used in the downstream supervised training.
A UMAP embedding plot is generated by Embed Patches with the current latest model. The user can View Embedding plot which helps to select patches for annotation which are dispersed in the model space.