JCruan519 / MALUNet

(BIBM22) This is the official code repository for "MALUNet: A Muti-Attention and Light-weight UNet for Skin Lesion Segmentation".

MALUNet

This is the official code repository for "MALUNet: A Muti-Attention and Light-weight UNet for Skin Lesion Segmentation", which is accpeted by IEEE International Conference on Bioinformatics and Biomedicine (BIBM2022) as a regular paper! [arxiv]

0. Main Environments

• python 3.8
• pytorch 1.8.0
• torchvision 0.9.0

1. Prepare the dataset.

• The ISIC17 and ISIC18 datasets, divided into a 7:3 ratio, can be found here {Baidu or GoogleDrive}.

• After downloading the datasets, you are supposed to put them into './data/isic17/' and './data/isic18/', and the file format reference is as follows. (take the ISIC17 dataset as an example.)

• './data/isic17/'

  • train
    • images
      • .png
    • masks
      • .png
  • val
    • images
      • .png
    • masks
      • .png

2. Train the MALUNet.

cd MALUNet

python train.py

3. Obtain the outputs.

• After trianing, you could obtain the outputs in './results/'