Leaderboard - First round

Based on the median rank profile for SSIM scores, the top five submissions from each task were assessed by a panel of radiographers and radiologists. The median rank profile of these observer quality scores (QS) determines the final ranking (QS-rank) for each task. The definition of the quality scores can be found under Evaluation.


Test Results - Task 1:

Place Team SSIM SSIM-Rank QS QS-Rank
1st SubtleMedical 0.1513   (Details) 2 3.7625   (Details) 3
2nd UVABME 0.2523   (Details) 3 2.875    (Details) 2
3rd Di Fan Team 0.0953   (Details) 1 1.075    (Details) 1


The columns SSIM and QS show average values across all test subjects. A file containing individual values is linked.


Test Results - Task 2:

Place Team SSIM SSIM-Rank QS QS-Rank
1st SubtleMedical 0.3050   (Details) 2 3.2375   (Details) 3
2nd UVABME 0.3666   (Details) 3 2.975    (Details) 2
3rd Di Fan Team 0.2805  (Details) 1 2.55       (Details) 1



Participating Teams:


Team Name Participants Description Details
Di_Fan_Team Di Fan Deep de-aliasaing generative adversarial network (DAGAN), SSIM loss MICCAI 2013 grand challenge and fastMRI dataset used for pre-training 
SubtleMedical Kevin Blansit, Zhehao Zhu,
Ben Duffy,
Keshav Datta
Deep convolutional neural network (DCNN), combined SSIM and L1 loss fastMRI dataset used for training
UVABME Quan Dou,
Xue Feng,
Craig Meyer
U-Net, combined SSIM and
L1 loss
fastMRI dataset used for training