Multi-rater Prism

A pytorch implementation of the paper 'Multi-rater Prism: Learning self-calibrated medical image segmentation from multiple raters' and 'Learning self-calibrated optic disc and cup segmentation from multi-rater annotations' accepted by MICCAI 2022

Preparation

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

Quick Start

Training:

python train.py -net transunet -exp_name test_train -mod rec

Inference:

python val.py -net transunet -mod rec -exp_name val_seg -weights 'recorded weights'

See cfg.py for more avaliable parameters

Todo list

• add requirement
• del debug code
• function name alignment
• del redundance
• release a slim version