PromptMR+ baselines (knee, CMRxRecon2023) + model card

README.md

@@ -21,11 +21,19 @@ Training and evaluation code: the loopmri repository, which downloads these file
 | `knee5_rs5_fd_100k.pt` | fastMRI knee, ×4 / ×8 |
 | `cmr23_rs5_fd_466k.pt` | CMRxRecon2023 cine and mapping, ×4 / ×8 / ×10 |
 | `knee5_sens_prefit/` | the SME pre-fit the knee training starts from |
+| `promptmr_plus/knee5_promptmr_plus_100k.pt` | PromptMR+ baseline, fastMRI knee |
+| `promptmr_plus/cmr23_promptmr_plus_466k.pt` | PromptMR+ baseline, CMRxRecon2023 |
+
+The two PromptMR+ models are the baselines of the paper's tables, trained by us with the authors' settings on the same data and
+schedule as LoopMR, because the authors' released knee and CMRxRecon2023 weights were trained on other data (fastMRI's full knee
+training set, and CMRxRecon2023 P001-P120, which includes the test patients). On CC359 the paper uses the authors' released weights
+([hellopipu/PromptMR](https://huggingface.co/hellopipu/PromptMR)), which are not copied here: the loopmri code downloads and converts
+them.
 
 ## Results
 
-PSNR (dB) / SSIM on the test sets, each dataset with its official protocol (CMRxRecon2023: all 76 test files at every R, as in the
-challenge). CC359 and knee were computed on an H100 and CMRxRecon2023 on an A100. The block runs in bf16, so on another GPU type
+PSNR (dB) / SSIM on the test sets, LoopMR and PromptMR+ both evaluated by the loopmri code, each dataset with its official protocol
+(CMRxRecon2023: all 76 test files at every R, as in the challenge). CC359 and knee were computed on an H100 and CMRxRecon2023 on an A100. The block runs in bf16, so on another GPU type
 PSNR can differ by about 0.01 dB in these means.
 
 | dataset | R | LoopMR | PromptMR+ |
@@ -40,5 +48,5 @@ PSNR can differ by about 0.01 dB in these means.
 
 ## Licence
 
-CC BY-NC 4.0. The models were trained on CC359, fastMRI and CMRxRecon2023 data, whose terms of use apply, and use PromptMR+'s SME
-(Rutgers non-commercial research licence). Research use only, not for clinical use.
+CC BY-NC 4.0. The models were trained on CC359, fastMRI and CMRxRecon2023 data, whose terms of use apply, and use PromptMR+'s code
+(Rutgers non-commercial research licence): its SME in LoopMR, the whole network in the PromptMR+ baselines. Research use only, not for clinical use.

promptmr_plus/cmr23_promptmr_plus_466k.pt

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promptmr_plus/knee5_promptmr_plus_100k.pt

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