SOTA PI reconstruction on Anatomical T1 contrast out-of-distribution and PapersWithCode

38.33PSNR

fully-learned filters and time conditioning (FLF+TC)

Updated 22d ago

Evaluation Results

Method
fully-learned filters and time conditioning (FLF+TC) 2026.05	38.33	94	0.38
fully-learned filters (FLF) 2026.05	38.28	94	0.38
fully-learned filters (FLF) 2026.05	37.72	94	0.43
fully-learned filters and time conditioning (FLF+TC) 2026.05	37.63	94	0.44
Shearlet (SH) 2026.05	37.49	94	0.45
Shearlet (SH) 2026.05	37.29	94	0.47
fully-learned filters (FLF) 2026.05	36.82	93	0.53
fully-learned filters and time conditioning (FLF+TC) 2026.05	36.75	93	0.54
total variation 2026.05	36.63	94	0.55
Shearlet (SH) 2026.05	35.96	93	0.64
total variation 2026.05	35.88	92	0.67
fully-learned filters and time conditioning (FLF+TC) 2026.05	35.85	93	0.68
fully-learned filters (FLF) 2026.05	35.65	92	0.71
total variation 2026.05	35.49	92	0.72
fully-learned filters and time conditioning (FLF+TC) 2026.05	35.28	93	0.78
Zero filled 2026.05	34.86	90	0.86
fully-learned filters (FLF) 2026.05	34.82	92	0.86
Shearlet (SH) 2026.05	34.55	91	0.92
total variation 2026.05	33.43	91	1.19
Shearlet (SH) 2026.05	33.41	91	1.21
end-to-end variational network 2026.05	32.09	84	1.5
total variation 2026.05	32.01	90	1.66
end-to-end variational network 2026.05	29.55	81	2.68
Zero filled 2026.05	29.37	78	3.19
Zero filled 2026.05	28.5	80	4.01
Zero filled 2026.05	28.49	78	3.91
Zero filled 2026.05	25.19	70	8.73
end-to-end variational network 2026.05	22.15	56	11.86
Deep-JSense 2026.05	21.29	73	81.67
end-to-end variational network 2026.05	20.72	44	14.59
end-to-end variational network 2026.05	16.19	42	27.61
Deep-JSense 2026.05	-4.18	45	47.9
Deep-JSense 2026.05	-8.81	41	55.55
Deep-JSense 2026.05	-46.05	5	94.91
Deep-JSense 2026.05	-48.59	4	98.19