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Opinions Vary? Diagnosis First!

This is a pytorch implementation of paper "Opinions Vary? Diagnosis First!". We propose a novel method to learn the diagnosis-first segmentation from the multiple labeled data. This method beat the popular majority vote by a large margin.

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Preparation

The code is run on pytorch1.8.1 + cuda 10.1.

Quick Start

Generate DFSim:

python val.py -net 'your_backbone' -mod val_ad -exp_name generate_dfsim -weights 'weights of diagnosis network'

Train Segmentation:

python train.py -net transunet -mod seg -exp_name repro_seg -base_weights 'weights of diagnosis network'

Segmentation Inference:

python val.py -net 'backbone' -mod set -exp_name val_seg -weights 'recorded weights'

See cfg.py for more avaliable parameters