Add training folds - Githubissues

spinalcordtoolbox / disc-labeling-hourglass

Labeling of intervertebral discs using the Hourglass deep learning architecture.

GNU Lesser General Public License v2.1

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Add training folds #21

Open NathanMolinier opened 1 year ago

NathanMolinier commented 1 year ago

Description

Currently, the hourglass network is trained on a single "fold" corresponding to only one split of a dataset (train/validation/test). To improve the ability of the network to generalise, multiple splits could be used for the same dataset and then averaged to improve the robustness of the predictions.

jcohenadad commented 1 year ago

Average is tricky (bc if binary hot-encoded labels that wouldn't be compatible)-- other stragegy: majority voting-- MONAI or pytorch has that-- see example https://github.com/ivadomed/model_seg_mouse-sc_wm-gm_t1/blob/f5750a9c6cd85c3b5d3d08a15b2ee3820c53440b/test.py#L98-L106