Skip to content

Latest commit

 

History

History
21 lines (12 loc) · 854 Bytes

README.md

File metadata and controls

21 lines (12 loc) · 854 Bytes

Data-Centric-Diet

This repository accompanies the paper Data-Centric Diet: Effective Dataset Pruning for Medical Image Segmentation and contains the basic code for replicating the training and computations in it. We found easy and hard to learn example for deep learning model by DAD(Dynamic average dice) Score.

Usage

The main requirements are pytorch 1.4.0 with python 3.9.1.

Training on single dataset

To train one independent run of 3D-UNet on MSD-Pancreas (the full dataset), first set up params args.dataset='msd' in params_msd_only, then from <ROOT> execute

python run/train_vnet.py 

ATTENTION

This is a demo presentation that may encounter bugs or issues that may not run properly. The complete code will be released after the paper is received.