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Model Zoo and Baselines

Model Zoo and Baselines#

Introduction#

This file documents baselines created with the DIRECT project. You can download the parameters and weights of these models in a .zip file by pressing on the hyperlink of the checkpoint. Each file contains the model checkpoint(s), a configuration file config.yaml with the model parameters used to load the model for inference and validation metrics.

How to read the tables#

  • “Name” refers to the name of the config file which is saved in projects/{project_name}/configs/{name}.yaml

  • Checkpoint is the integer representing the model weights saved in model_{iteration}.pt as that iteration.

License#

All models made available through this page are licensed under the
 Creative Commons Attribution-ShareAlike 3.0 license.

Baselines#

Calgary-Campinas MR Image Reconstruction Challenge#

Models were trained on the Calgary-Campinas brain dataset. Training included 47 multicoil (12 coils) volumes that were either 5x or 10x accelerated by retrospectively applying masks provided by the Calgary-Campinas team.

Validation Set (12 coils, 20 Volumes)#

Model

Name

Acceleration

Checkpoint

SSIM

pSNR

VIF

NMSE

RecurrentVarNet

recurrentvarnet

5x

148500

0.943

36.1

0.964

-

RecurrentVarNet

recurrentvarnet

10x

107000

0.911

33.0

0.926

-

LPDNet

lpd

5x

96000

0.937

35.6

0.953

-

LPDNet

lpd

10x

97000

0.901

32.2

0.919

-

IterDualNet

iterdualnet

5x

33500

0.936

35.2

0.973

0.0051

IterDualNet

iterdualnet

10x

33500

0.898

31.9

0.930

0.0112

ConjGradNet

conjgradnet

5x

55000

0.937

35.51

0.964

0.0047

ConjGradNet

conjgradnet

10x

50500

0.918

32.3

0.918

0.010

RIM

rim

5x

89000

0.932

35.0

0.964

-

RIM

rim

10x

63000

0.891

31.7

0.911

-

VarNet

varnet

5x

4000

0.917

33.3

0.937

-

VarNet

varnet

10x

3000

0.862

29.9

0.861

-

Joint-ICNet

jointicnet

5x

43000

0.904

32.0

0.940

-

Joint-ICNet

jointicnet

10x

42500

0.854

29.4

0.853

-

XPDNet

xpdnet

5x

16000

0.907

32.3

0.965

-

XPDNet

xpdnet

10x

14000

0.855

29.7

0.837

-

KIKI-Net

kikinet

5x

44500

0.888

29.6

0.919

-

KIKI-Net

kikinet

10x

44500

0.833

27.5

0.856

-

MultiDomainNet

multidomainnet

5x

50000

0.864

28.7

0.912

-

MultiDomainNet

multidomainnet

10x

50000

0.810

26.8

0.812

-

U-Net

unet

5x

10000

0.871

29.5

0.895

-

U-Net

unet

10x

6000

0.821

27.8

0.837

-

CMRxRecon Challenge 2023 (Test Dataset)#

Task 1 (Cine)#

Model

Name

Checkpoint

SSIM

pSNR

NMSE

vSHARP 3D

vSHARP_2D_dynamic

325000

0.988

46.2

0.0037

Task 2 (Mapping)#

Model

Name

Checkpoint

SSIM

pSNR

NMSE

vSHARP 3D

vSHARP_2D_dynamic

325000

0.984

44.4

0.0043
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