/liver_segmentation

Unet,Unet++,FPN,DAF implementations for liver segmentation

Primary LanguagePython

Liver segmentation models

Table of content

  1. Architectures
  2. Experiment results
  3. ...

Architectures

  • Unet
  • Unet++
  • FPN
  • DAF

Experiment results

We test these four segmentation models at a liver datasets. We rewrite the framework with reference to DAF. The model implementations of Unet,FPN and DAF are dependent on github while Unet++ is implemented by ourself. For fair, we train all models with 60 epochs and add evaluation for each epoch. Then save best epoch as the last result. We evaluate them with two norm: Dice and F1, all results as follows:

Model Dice F1 Backbone Batch size Loss function Resize Use pretrained Rcf refine
Unet 0.9494 0.9503 Resnet-18 4 bcd,dice (448,448) Y Y
Unet++ 0.9453 0.9465 Resnet-18 8 bcd,dice (224,224) Y Y
FPN 0.9493 0.9491 Resnet-18 4 bcd,dice (448,448) Y Y
DAF 0.9515 0.9515 ResNext-101 4 bcd,dice (448,448) Y Y