https://github.com/axondeepseg/model_seg_unmyelinated_tem - Stanford model

result of 3rd training pass on the Stanford data

This release contains an ensemble of 5 nnunet models. This model segments myelinated and unmyelinated axon fibers, as well as nuclei and processes. Only the best checkpoints (wrt. validation score) are included.

This is a prediction example, with unmyelinated axons in green.

- Python
Published by hermancollin almost 2 years ago

https://github.com/axondeepseg/model_seg_unmyelinated_tem - Full model trained on data from SickKids Foundation

These are the final results of the training performed on the SickKids Foundation data (UoT) for unmyelinated axon segmentation on TEM images. Two versions are included: - best contains the model checkpoints that achieved the best validation score during training - last contains the last model checkpoints after 1000 epochs

Usually, the best checkpoints perform better, but your mileage may vary. Both versions contain 5 models from the 5-fold cross-validation scheme, for ensembling.

- Python
Published by hermancollin over 2 years ago

https://github.com/axondeepseg/model_seg_unmyelinated_tem - First nnUNet model release

This release contains a model checkpoint from one of the 5 cross-validation folds. The checkpoint was trained on data_axondeepseg_sickkids (for more information, see the sickkids_pipeline folder.

Please note that this model is only 1 validation fold, which does not perform as well as the 5 folds ensembled. For more information, see #1.

- Python
Published by hermancollin over 2 years ago