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Repository to collect all the references on generation of synthetic computed tomography (sCT) with deep learning/convolutional networks. Generated from Spadea MF, Maspero M et al Med. Phys. 2021

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# Overview sCT

Repository to collect all the references on generation of synthetic computed tomography (sCT) with deep learning/convolutional networks. Generated from Spadea MF & Maspero M et al. Med. Phys. 2021 (in press), [https://doi.org/10.1002/mp.15150](https://doi.org/10.1002/mp.15150), preprint at: [http://arxiv.org/abs/2102.02734](http://arxiv.org/abs/2102.02734). This page is available at: [https://matteomaspero.github.io/overview_sct/](https://matteomaspero.github.io/overview_sct/) and its Github repository is: [https://github.com/matteomaspero/overview_sct/](https://github.com/matteomaspero/overview_sct/).

**By the end of 2021 the table will be updated, so far all the paper up to Jan 2021 should be included, if not; please, feel free to contribute!**

## License
[![CC BY-SA 4.0][cc-by-sa-shield]][cc-by-sa]

[cc-by-sa]: http://creativecommons.org/licenses/by-sa/4.0/
[cc-by-sa-image]: https://licensebuttons.net/l/by-sa/4.0/88x31.png
[cc-by-sa-shield]: https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg

This work is licensed under a
[Creative Commons Attribution-ShareAlike 4.0 International License][cc-by-sa].

[![CC BY-SA 4.0][cc-by-sa-image]][cc-by-sa]

In short, this means that anyone, even a commercial entity may re-use the content of this page as long as it will cite our paper and the source.

## Contributors

Maspero M is the owner administrator of the project. Spadea Maria Francesca and Paolo Zaffino greatly contributed to the data collection for the publication.

The following added content: ...

## Make the table sortable

If you wish to extend the interaction with the tables, you can sort the columns in your favourite browser, as described [here](https://github.com/Mottie/GitHub-userscripts/wiki/GitHub-sort-content). We have tested on Chrome the following combination:
* install [Tampermonkey](https://chrome.google.com/webstore/detail/tampermonkey/dhdgffkkebhmkfjojejmpbldmpobfkfo/related);
* install [Github Sort Content](https://greasyfork.org/en/scripts/21373-github-sort-content);

## If you see any typos/mistakes

Ok, we did our best, but you got us! That can happen, but you can contribute to the accuracy of the information in this page by proposing a commit, after having forked this repository. Matteo will keep monitored the repository and update it every two months.
If you wish to see some changes, just reach out; we are more than happy to hear your comments/suggestions.

## MRI without dose evaluation

| Tumour site | train | val | test | x-fold | field [T] | sequence | conf | arch | Reg | MAE [HU] | PSNR [dB] | SSIM | others | reference | pub date |
|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
Abdomen |	10v	|		|	10	|	LoO	|		|	mDixon |	2D pair	|	GAN\* |	def	|	61±3	|		|		|	CC | [Xu2019](https://doi.org/10.1109/ACCESS.2019.2951924) | 2019-11-06 |
Abdomen |	160	|		|		|	 LoO |	n.a.	|	n.a.	|	2D pair	|	GAN\*	|	rig	|	 5.1±0.5	|		|	.90±.43	| (F/M)SIM IS ...	| [Xu2020](https://doi.org/10.1016/j.neunet.2020.05.001) | 2020-05-08 |
Brain	|	18	|		|		|	6x	|	1.5 |	3D T1 GRE		|	2D	pair |	U-net		|	rig	|	85±17	|		|		|	MSE ME	| [Han2017](https://doi.org/10.1002/mp.12155)	| 2017-02-13 |
Brain |	16	|		|		|	LoO	|	n.a.	|	T1	|	2.5Dp patch	|		CNN+ 	|	rig	|	85±9	|	27.3±1.1	|		| | [Xiang2018](https://doi.org/10.1016/j.media.2018.03.011)	| 2018-03-30 | 
Brain	|	15	|		|		|	x5	|	1.0	|	T1 Gd	|	2D pair	|		GAN\* 	|	def	|	89±10	|	26.6±1.2	|	.83±.03	| tissues | [Emami2018](https://doi.org/10.1002/mp.13047)	| 2018-06-14 |
Brain	|	98CT 84MR 	|		|	10	|		|	3	|	3D T2	|	2D pair/unp |		GAN	|	aff	|	19±3	|	65.4±0.9	|	.25±.01	|		| [Jin2019](https://doi.org/10.3390/s19102361) | 2019-05-22 |
Brain 	|	24	|		|		|	LoO	|	n.a.	|	T1 |	3Dp pair	|	GAN	|	rig	|	56±9	|	26.6±2.3	|		|	NCC, HD body	| [Lei2019](https://doi.org/10.1002/mp.13617) | 2019-05-21 |
Brain	|	33 160	|		|		|	LoO	|	n.a. n.a.	|	T1b n.a.	|	2D	|	GAN	|	yes no	|	9.0±0.8 5.1±0.5	|		|	.75±0.77 .90±.43	| FSIM MSIM IS SWD FID experts	| [Xu2020](https://doi.org/10.1016/j.neunet.2020.05.001) | 2020-05-08 |
Brain	|	28t	|	2	|	15 |		|	1.5	|	n.a.	|	2D	|	GAN\*		|	aff	|	134±12 | 24.0±0.9	| .76±.02	|		| [Yang2020](https://doi.org/10.1109/tmi.2020.3015379) | 2020-11-30 |
Brain	|	28	|		|	6	|		|	1.5	|	T2	|	2D pair 2D unp	|	U-net GAN	| rig |	65±4 94±6	|	28.8±0.6 26.3±0.6	| .972±.004 .955±0.007	| same metrics for synth MRI |[Li2020](https://doi.org/10.1155/2020/5193707) | 2020-11-05|
Brain	|	81	|		|	11	|	8x	|	1.5	|	3D T1 GRE 3D T1 GRE Gd 2D T2 SE 2D T2 FLAIR 	|	2D	|	U-net 	|	aff | 45.4±8.5 44.6±7.4 45.7±8.8 51.2±4.5 | 43.0±2.0 43.4±1.2 43.4±1.2 44.9±1.2	| .65±.05 .63±.03 .64±.03 .61±.04	|	metrics for air bone, soft tissue, DSC bones	| [Massa2020](https://doi.org/10.1088/1361-6560/abc5cb) | 2020-11-27|
H&N	|	23	|		|	10	|		|	1.5|	T2	|	2D pair	|	U-net	|	def	|	131±24	|		|		|	MAE, ME soft tis./bone | [Wang2019](https://doi.org/10.3389/fonc.2019.01333) | 2019-11-29|
H&N	|	28	|	4	|		|	8x	|	1.5	|	2D T1±Gd, T2	|	2D pair	|	GAN	|	aff	|	75.7±14.6	|	29.1±1.6	|	.92±.02	|	DSC, MAE on bone	| [Tie2020](https://doi.org/10.1002/mp.14062)|2020-02-03 |
H&N	|	60			|	30	|		|	3	|	T1	|	2D	unp |	GAN	|	n.a.	|	19.6±0.7	|	62.4±0.5	|	.78±0.2	|		| | [Kearney2020](https://doi.org/10.1148/ryai.2020190027) | 2020-03-25 |
H&N	|	7	|		|	8	|	LoO	|	1.5	|	3D T1, T2	|	2D pair|		GAN	|	def	|	83±49	|		|		|	ME	|	[Largent2020](https://doi.org/10.1016/j.canrad.2020.01.008)| 2020-03-14 |
H&N	|	10	|		|		|	LoO	|	1.5	|	3D T1, T2	|	2D	pair|	GAN\*	|	def	|	42-62	|		|		|	RMSE, CC	| [Qian2020](https://doi.org/10.1007/s10723-020-09513-3) | 2020-03-10 |
H&N	|	32	|		|	8	|	5x	|	3	|	3D UTE	|	2D pair	|	U-net	|	def	|	104±21	|		|		|	DSC, spatial corr	| [Su2020](https://doi.org/10.3174/ajnr.A6758) | 2020-10-06 |
Prostate	|	16 22	|		|		|	LoO	|	n.a.	|	T1	|	2.5Dp pair	|		CNN+ 	|	rig	|	85±9 43±2	|	27.3±1.1 33.5±0.8	|		| | [Xiang2018](https://doi.org/10.1016/j.media.2018.03.011)	| 2018-03-30 
Pelvis	|	20	|		|		|	LoO	|	n.a.	|	3D T2 |	3Dp pair	|	GAN\*	|	rig	|	51±16	|	24.5±2.6	|		|	NCC, Hausdorff on body	| [Lei2019](https://doi.org/10.1002/mp.13617) | 2019-05-21 |
Prostate	|	20	|		|		|	5x	|	1.5	|	2D T1 TSE	|	2D pair 3D p pair	|		U-net	|	def	|	41±5 38±5	|		|		|	DSC bone 	| [Fu2019](https://doi.org/10.1002/mp.13672)| 2019-06-20 |
Pelvis human Pelvis canine	|	27 18	|		|		|	3x	|	3 1.5	|	3D T1 GRE mDixon 	|	3Dp pair	|		U-net	|	def	|	32±8	|	36.5±1.6	|		|	MAE/DSC bone surf dist<0.5 mm | [Florkow2019](https://doi.org/10.1002/mrm.28008) | 2019-10-08 |
Pelvis	|	15	|		|	4	|	5x	|	3	|	3D T2	|	2D	pair |	CNN U-net		|	def	|	38±6 43±9	|	29.5±1.2 28.2±1.6 	|	.96±.01 .95±.01	|	ME, PCC	| [Bahrami2020](https://doi.org/10.1002/mp.14418) | 2020-07-30 |
Pelvis	|	100	|		|	 |		|	3	|	2D T2 FSE	|	2D unp	|	GAN	|	No	|		|		|		|	FID	| [Fetty2020](https://doi.org/10.1016/j.zemedi.2020.05.001) | 2020-11 |
Breast	|	14	|		|	2	|	LoO	|	n.a. |	n.a. |	2D	|	U-net1	|	def	|	|	 |	 | DSC .74-.76 	| [Jeon2019](https://doi.org/10.14407/jrpr.2019.44.4.149) | 2019-12-31 |

**Super/subscripts** 
vvolunteers, not patients; 1to segment CT into 5-classes; amultiple combinations of Dixon images was investigated but omitted here; bdataset from http://www.med.harvard.edu/AANLIB/ ; trobustenss to training size was investigated;\*comparison with other architecture has been provided; +trained in 2D on multiple view and aggregated after inference; 
**Abbreviations** 
H&N=head and neck ; val=validation; x-fold=cross-fold ;conf=configuration; arch=architecture; GRE=gradient echo; (T)SE=(turbo) spin-echo, mDixon = multi-contrast Dixon reconstruction; LoO=leave-one-out; (R)MSE=(root) meas squared error; ME=mean error; DSC=dice score coefficient; (N)CC=normalized cross correlation; FSIM, MSIM, IS, SWD, FID, PCC look up the references ;)

## MRI-to-sCT with dose evaluation

| Tumour site | train | val | test | x-fold | field [T] | sequence | conf | arch | pair reg | MAE [HU] | PSNR [dB] | others| Plan | DD [%] | GPR [%] | DVH | others | reference | pub date |
|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
Liver	|	21	|		|		|	LoO	|	3	| 3D T1 GRE	|	3D pair| GAN	|	def	|	73±18	|	22.7±3.6	|		NCC | 	p	| | 99.4±1.03 | <1% | range γ2 γ1 | [LiuY2019](https://doi.org/10.1088/1361-6560/ab25bc) | 2019-06-16| 
Abdomen	|	12	|		 		| 	 |	4x	| 0.3 1.5 | GRE |	2D pair br> 2D unp| GAN\*	|	def	| 90±192 94±302 | 27.4±1.6 27.2±2.2| | 	x+B0	| <±0.6 	<±0.6 | 98.7±1.5% 98.5±1.6% | <±0.15 | γ 3 | [Fu2020](https://doi.org/10.1088/2057-1976/ab6e1f) | 2020-01-31 |
Abdomen	|	46	|		| 	31	| 3x	 |	3	| 3D T1 GRE |	2.5D pair | U-net	|	syn rig	| 79±18 | | MAE, ME organs |	x	| | | <2Gy | | [Liu2020](https://doi.org/10.1088/1361-6560/ab8cd2)| 2020-06-11 | 
Abdomen kids	|	54	|	18	| 12		|	 3x |	1.5	3| 3D T1 GRE, T2 TSE |	3Dp pair | U-net	|	def	| 62±13 | 30.0±1.8	| ME, DSC tissues | 	x p| <0.1 <0.5 | 99.7±0.32 96.2±4.02 | <2% <3% | beam depth | [Florkow2020](https://doi.org/10.1016/j.radonc.2020.09.056) | 2020-10-07
Abdomen |	39 	|		| 	19	|	 |	0.35	| GRE |	2D pair | U-net	|	def	| 79±18 | | ME tissues |	x+B0| <0.1 | 98.7±1.12 | <2.5% | γ3 γ1 | [Cusumano2020](https://doi.org/10.1016/j.radonc.2020.10.018) | 2020-10-17 | 
Brain	|	26	|		|		|	2x	|	1.5	| 3D T1 GRE	|	m2D+ pair | CNN	|	rig	|	67±11	|		|		ME, tissues DSC, dist body |	x	| -0.1±0.3 | 99.8±0.72 | | beam γ 3 depth γ1| [Dinkla2018](https://doi.org/10.1016/j.ijrobp.2018.05.058) | 2018-11 | 
Brain	|	40	|		|	10	|		|	1.5	| 3D T1 GRE Gd |	2D pair | CNN	|	def	|	75±23	|	|		DSC | 	x	| <0.2±0.5 | 99.23 | | | [LiuF2019](https://doi.org/10.1002/acm2.12554) | 2019-03-12 | 
Brain	|	54	|	9	|	14	|	5x	|	1.5	| 2D T1 SE Gd |	2D pair | GAN	|	rig	|	47±11	|	|		each fold |	x	| -0.7±0.5 | 99.2±0.82 | <1% | 2D/3D γ 3 γ1 | [Kazemifar2019](https://doi.org/10.1016/j.radonc.2019.03.026) | 2019-04-11 |
Brain	|	55	|28 |	4	|		|	1.5	| 3D T1 GRE	|	2D pair 3Dp pair | U-net	|	rig	|	116±26 137±32	|		|		ME | 	x p	| | >98^2,98±22 >98^2,97±32 | | range γ1 | [Neppl2019](https://doi.org/10.1080/0284186X.2019.1630754) | 2019-07-04| 
Brain	|	25	|	2	| 25		|		|	1.5	| 3D T1 GRE |	3Dp pair | GAN	|	rig	| 55±7 | 	|	 ME DSC|	x	| <2 | 98.4±3.52 | <1.65% | range γ 3 γ1| [Shafai2019](https://doi.org/10.14338/ijpt-19-00062.1) | 2019-09-30| 
Brain | 47 | | 13 | 5x | 3 | T1 | 2D pair | U-net | rig |81±15 | | ME air, tissues| x |2.3±0.1 | | | align CBCT<0.5mm | [Gupta2019](https://doi.org/10.3389/fonc.2019.00964) | 2019-10-25 | 
Brain	|	12	|	2	| 1		|	LoO	|	3	| 3D T1 GRE |	2D+ pair | U-net	|	rig	| 54±7 | 	|	 ME, DSC | p	| 0.00±0.01 | | | range tissues | [Spadea2019](https://doi.org/10.1016/j.ijrobp.2019.06.2535) | 2019-11-01 | 
Brain	|	15	|		 		| 	 |	5x	| | T1, T2 FLAIRc |	2Dp pair | GAN	|	def	| 108±24 | | tissues |	x	| 0.7 | 99.2±1.02 | <1% | beam depth γ3 γ1 | [Koike2019](https://doi.org/10.1093/jrr/rrz063) | 2019-12-10 | 
Brain	|	66	|		 		| 11	 |	5x	| 1.5 | 2D T1 SE Gd |	2D unp | GAN	|	rig	| 78±11 | | |	p	| 0.3±0.3 | 99.2±1.02 | <3% | beam γ3 depth γ1 | [Kazemifar2020](https://doi.org/10.1002/acm2.12856) | 2020-03-26 | 
Brain kids	|	30t	|	10	| 20		|	 3x |	1.5 3	| 3D T1 GRE±Gd |	 2D+\* pair | GAN\*	|	rig	| 61±14 | 26.7±1.9	| ME DSC SSIM | 	x	 p| -0.1±0.3 0.1±0.4 | 99.5±0.82 99.6±1.12 | <1% <3% | beam depth γ3 | [Maspero2020](https://doi.org/10.1016/j.radonc.2020.09.029) | 2020-10-23 | 
Brain	|	242m,t	|		 	81	| 79	 |		| 3 1.5| 3D T1 GRE±Gd |	3Dp pair| CNN U-net	|	def	| 81±22 90±21 | |tissues |	x	| 0.13±0.13 0.31±0.18 | 99.6±0.32 99.4±0.52 | <±0.15 | γ 3 | [Andres2020](https://doi.org/10.1016/j.ijrobp.2020.05.006) | 2020-11 |
Brain	|	26	|		 15		| 12	 |		| 1.0 | T1 Gd |	2D | GAN	|	def	| | | bone | 	x	| <±1 | | <1.5% | | [Liu2021](https://doi.org/10.1002/acm2.13139) | 2021-01-07| 
Prostate Rectum Cervix	|	32	|		|	27 18 14 |		|	3 1.5 1.5/3	|	3D T1 GRE mDixon 	|	2D pair	|	GAN |	rig	|	60±6 56±5 59±6 |	|		ME | x	| -0.3±0.4 -0.3±0.5 -0.1±0.3a | 99.4±0.63 98.5±1.13 99.6±1.93|<1% | γ2 | [Maspero2018](https://doi.org/10.1088/1361-6560/aada6d) | 2018-09-10| 
Prostate| 36 | | 15 | | 3 | T2 TSE | 2D pair | U-net | def |	30±5 |	|		ME tissues | 	x	| 0.16±0.09 | 99.42 | <0.2Gy | γ3 γ1| [Chen2018](https://doi.org/10.1002/mp.13247) | 2018-10-20 |
Prostate | 39 | | | 4x | 3 | 3D T2 | 2D pair | U-net | def |33±8 | |ME, DSC dist body | x |-0.01±0.64 | 98.5±0.72 | <3% | γ3 γ1| [Arabi2018](https://doi.org/10.1002/mp.13187) | 2018-10-14 |
Prostate	|	17	|		|		|	LoO	|	1.5	| T2 |	3D patch | GAN\*	|	No	|	51±17	| 24.2±2.5	|	 NCC, bone:dist, uniform	 | 	p	| -0.07±0.07 | 98±62 | <1% | range peak γ 3 γ1| [LiuY2019b](https://doi.org/10.1088/1361-6560/ab41af) | 2019-10-21 | 
Prostate	|	25	|		| 	14	|	3x	|	3	| 3D T2 TSE |	2D | U-net\* GAN\*	|	def	| 34±8 34±8 | 	|	 ME tissues | 	x	| <1% <1% | 99.2±11 99.1±11 | <1% | | [Largent2019](https://doi.org/10.1016/j.ijrobp.2019.08.049) | 2019-12-1 | 
Pelvis	|	11m	|		 		| 8	 |		| 3 1.5| T2 TSE |	2D | GAN\*	|	def	| 49±6 | | ME organs | 	x	| 0.7±0.4 | 99.2±1.02 | <1.5% | | [Boni2020](https://doi.org/10.1088/1361-6560/ab7633) | 2020-04-02 | 
Pelvis	|	26	|		 15		| 10+19m	 |		| 0.35 1.5/3 | 3D T2 |	2.5D | GAN\*	|	def	| 41±4 | 31.4±1 | ME MSE bone | 	x	| <±1 | | <1.5% | | [Fetty2020](https://doi.org/10.1088/1361-6560/ab857b) | 2020-05-22| 
Pelvis	|	39	|		| 14	|	 |	0.35	| GRE |	2D pair| U-net	|	def	| 54±12 | | ME tissues |	x+B0| <0.5 | 99.0±0.72 | <1% | γ3 γ1 | [Cusumano2020](https://doi.org/10.1016/j.radonc.2020.10.018) | 2020-10-17 | 
Rectum	|	46m	|		 		| 44	 |		| 1.5 | 3D T2 |	2D | GAN	|	def	| 35±7 | | ME bone | 	x	| <±0.8 | 99.8±0.12 | <1% | γ 3 γ1 | [Bird2020](https://doi.org/10.1016/j.radonc.2020.11.027) | 2020-11-29 | 
H&N	|	34	|		|		|	3x	|	1.5	| 3D T2 TSE	|	3Dp pair | U-net	|	def	|	75±9	|		|		ME DSC bone | 	x	| -0.07±0.22 | 95.6±2.92 | | γ 3 | [Dinkla2019](https://doi.org/10.1002/mp.13663) | 2019-06-17 |
H&N	|	15	|		| 12		|	|	3	| T1 GRE |	2Dp pair\* | GAN\*	|	def	| | 68±2	| SSIM RMSE | 	p	| <0.5 | <982 | <0.5 | | [Klages2019](https://doi.org/10.1002/mp.13927) |2019-11-16 | 
H&N	|	30	|		| 15		|	|	3	| T1±Gd T2 TSEc |	2D pair | GAN\* U-net	|	rig	| 70±12 71±12 | 29.4±1.3 29.2±1.3 	| SSIM DSC, DRR | 	p	| -0.3±0.2 -0.2±0.2 | 97.8±0.92 97.6±1.32 | | | [Qi2020](https://doi.org/10.1002/mp.14075) | 2020-02-06| 
H&N	|	135t	|	10	| 28		|	 |	3	| 3D T1 GRE |	2D pair unp | GAN\*	|	def	| 70±9 101±8 | 	| ME, DSC tissues | 	x	| -0.1±0.3 0.1±0.4 | 98.7±1.02 98.5±1.12 | <1.5% <1.5% | beam depth | [Peng2020](https://doi.org/10.1016/j.radonc.2020.06.049) |2020-07-03 |
H&N	|	27	|		 | 	 |	3x	| 3 | 3D T1 GRE |	2D+ pair | GAN	|	def	| 65±4 | | ME | 	p	| <±0.2 | 93.5±3.4| <1.5% | NTCP DSC RS γ3 | [Thummerer2020](https://doi.org/10.1088/1361-6560/abb1d6)| 2020-11-27|
Breast	|	12t	|		| 18		|	LtO	|	1.5	| 3D GRE mDixon |	2D + patch | GAN\*	|	def	| 94±11 103±15 | 	|	 NCC | p	| <0.5 | 98.4±3.52 | | DRR dist bone | [Olberg2019](https://doi.org/10.1002/mp.13927) | 2019-11-16 |

**Super/subscripts** 
\*comparison with other architecture has been provided; 3γ3%,3mm = γ3; 2γ2%,2mm = γ2; 1 γ1%,1mm = γ1; trobustenss to training size was investigated; +trained in 2D on multiple view and aggregated after inference; c multiple combinations (also ± Dixon reconstruction, where present) of the sequences were investigated but omitted;
m data from multiple centers 
**Abbreviations** 
H&N=head and neck ; val=validation; x-fold=cross-fold ;conf=configuration; arch=architecture; GRE=gradient echo; (T)SE=(turbo) spin-echo, mDixon = multi-contrast Dixon reconstruction; LoO=leave-one-out; (R)MSE=(root) meas squared error; ME=mean error; DSC=dice score coefficient; (N)CC=normalized cross correlation;

## CBCT

| Tumour site | train | val | test | x-fold | conf | arch | pair reg | MAE [HU] | PSNR [dB] |SSIM | others| Plan | DD [%] | DPR [%] |GPR [%] | DVH | others | reference | pub date |
|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
Pancreas | 30 | | | LoO | 3Dp pair | GAN\* | def | 56.89±13.84 | 28.80±2.46 | .71±.032 | NCC| SNU | x | | | <1Gy | | [Liu2020](https://doi.org/10.1002/mp.14121) | 2020-03-06|
Brain Pelvis | 24 20 | | | LoO | 3D patch | GAN | rig | 13±2 16±5 | 37.5±2.3 30.7±3.7| | NCC SNU | No | | | | | |[Harms2019](https://doi.org/10.1002/mp.13656)| 2019-06-17 | 
Prostate | 16 | | 4 | 5x | 2D pair | U-net | def | | 50.9 |.967 | SNU RMSE | No | || | | | [Kida2018](https://doi.org/10.7759/cureus.2548) | 2018-04-29| 
Prostate | 27 | 7 | 8 | | 2D pair | U-net\* | def | 88 | | | ME| x p| | >98.41 88.53 | 99.52 >96.52 | | γ 1 DPR 2 | [Landry2019](https://doi.org/10.1088/1361-6560/aaf496) | 2019-01-24 |
Prostate | 18 | | 8 | 4x | 2D ens unp | GAN | No| rig | 87±5 | | | ME | x p| 99.9±0.32 80.5±52 | 95.9±2.02 | <±1.5% <1% | DPR1 DPR3 RS γ3 | [Kurz2019](https://doi.org/10.1088/1361-6560/ab4d8c) | 2019-11-15|
Prostate | 16 | | 4 | | 2D pair | GAN\* | rig | | | | SelfSSIM tissues | No | | | | | | [Kida2019](https://doi.org/10.1002/mp.13963) | 2019-12-16|
Pelvis H&N| 135 | 15 | 15 10 | 10x | 2.5D pair | GAN\* | def | 24±5 24±4 | 20.1±3.4 22.8±3.4 | | | x, p | <1% | | | | RS | [Zhang2020](https://doi.org/10.1002/mp.14624) |2020-12-01 | 
H&N Lung Breast | 15 15 15 | 8 8 8 | 10 10 10 | | 2D | GAN\* | No rig | 53±12 83±10 66±18 | 30.5±2.2 28.5±1.6 29.0±2.1 | .81±.04 .78±.04 .76±.02 | ME | x | 0.1±0.5 0.2±0.9 0.1±0.4 | | 97.8±12 94.9±32 92±82 | <2% | γ 3 | [Maspero2020](https://doi.org/10.1016/j.phro.2020.04.002) | 2020-04-29 | 
H&N | 81 | 9 | 20 | | 2D | GAN\* | No def | 29.85±4.94 | 30.65±1.36 | .85±.03 | RMSE phantom | x | | | 98.4±1.72 96.3±3.61 | | | [Liang2019](https://doi.org/10.1088/1361-6560/ab22f9) | 2019-06-10 | 
Nasophar| 50 | 10 | 10 | | 2D | U-net | rig | 6-27| | | ME organs | x | 0.2±0.1| |95.5±1.61 | <1% | | [Li2019](https://doi.org/10.1088/1361-6560/ab2770) | 2019-07-16 | 
H&N | 30 | 7 | 7 | | 2D | U-net\* | rig | 18.98| 33.26 | 0.8911| RMSE tissues | No | | | | | | [Chen2019](https://doi.org/10.1002/mp.13978) | 2019-12-18 | 
H&N | 30 | | 14 | | 2D | GAN | def | 82±11 | | | ME tissues | x | 91.0±5.32 | | <1Gy| <1% | | [Barateau2020](https://doi.org/10.1002/mp.14387)| 2020-07-12 | 
H&N | 22 | | 11 | 3x | 2D+ | U-net | def | 36±6 | | | ME DSC SNU | p | -0.1±0.3 | | 98.1±1.22 | | RS γ 3 |[Thummerer2020](https://doi.org/10.1088/1361-6560/ab7d54) | 2020-04-27| 
H&N | 50t | | 10 | | 2.5D | U-net | rig | 49 | | .85 | SNR | No | | | | | | [Yuan2020](https://doi.org/10.1088/1361-6560/ab6240) |2020-01-24| 
H&N | 23 | | | LoO | 3D patch | GAN\* | rig | | 24.3±1.4| .80±.05 | stop power | p | | | 88.42 | <1% | γ3 γ2 | [Harms2019](https://doi.org/10.1002/mp.14347)| 2019-06-17 |
H&N Thorax Pelvis | 25 53 205 || | 15 15 15 | 2D | GAN | def | 77±13 94±32 42±5 | | | ME DSC HD tissues | x | | 91.5±4.32 76.7±17.32 88.9±9.32 | 95.0±2.42 93.8±5.92 98.5±1.72 | <2.4 <2.6 <1 | γ 3 | [Eckl2020](https://doi.org/10.1016/j.ejmp.2020.11.007) | 2020-11-24 |

----------------------

## PET

| Region | train | val | test | x-fold | field [T] | image contrast | conf | arch | pair reg | MAE [HU] | DSC | tracer| PETerr [%] | others | reference | pub date|
|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
Pelvis| 10 | | 16 | | 3 | Dixon ZTE | 3D patch | U-net | def | | | 18F-FDG 68Ga-PSMA || RMSE SUV diff | [Leynes2017](https://doi.org/10.2967/jnumed.117.198051) |2017-05-01 |
Head | 30 | | 10 | | 1.5 | T1 GRE Gd | 2D | auto-enc | def | .971±.005a .936±.011s| .803±.021b |n.a. | -0.7±1.1 | | [Liu2018](https://doi.org/10.1148/radiol.2017170700) | 2017-10-19 |
Pelvis| 12 | | 6 | | 3 | T1 GRE T2 TSE | 3D | CNN1 | def | | .98±.01s .79±.03b .49±.17a | 18F-FDG | | RMSE | [Bradshaw2018](http://dx.doi.org/10.18383/j.tom.2018.00023) | 2018-09 |
Head | 30p+6 | | 8 | | | UTE mDixon | 2D | U-net1 | def | | .96±.006b | 18F-FDG| <1% | | [Jang2018](https://doi.org/10.1002/mp.12964) | 2018-5-15 |
H&N | 32 12 | | 8 2 | 5 7 | 3 | Dixon±ZTE | 2D | U-net | rig | 13.8±1.4 12.6±1.5 | .76±.04b .80±.04b | 18F-FDG | <3 | | [Gong2018](https://doi.org/10.1088/1361-6560/aac763) | 2018-06-13 |
Pelvis| 15 | | 4 | 4 | 3 | T1 GRE Dixon | 2D | U-net | def | | |18F-FDG 1.8±2.4 | 1.7±2.0f 1.8±2.4s 3.8±3.9b | mu-map diff | [Torrado2019](https://doi.org/10.2967/jnumed.118.209288) | 2018-08-30 |
Head | 23 | | 47 | | 3 | ZTE | 3D patch | U-net | def | | .81±.03b |18F-FDG | -0.2±5.6 | Jac | [Blanc-Durand2019](https://doi.org/10.1371/journal.pone.0223141) | 2019-10-07|
Head kids | 60 | | 19 | 4 | 3 | T1 GRE mDixon, UTE | 3D | U-net | rig | | .90±.07j |18F-FET | | biol tumor vol, SUV | [Ladefoged2019](https://doi.org/10.3389/fnins.2018.01005) | 2019-01-07 |
Head | 44 | 11 | 11 | | 1.5 | T1 GRE | 2.5D | U-net | rig | | |11C-WAY 11C-DASB | -0.49±1.7 | synt mu-map, kin anal | [Spuhler2019](https://doi.org/10.2967/jnumed.118.214320) | 2019-08-30 |
Head | 40 | | | 2 | 3 | 3D T1 GRE | 3D patch | GAN | def | 101±40 302±79b 407±228a 8±4s | .80±.07b | 18F-FDG|3.2±3.4 1.2±13.8b 3.2±13.6s 3.2±13.6a | rel vol dif surf dist ME RMSE PSNR SSIM SUV | [Arabi2019](https://doi.org/10.1007/s00259-019-04380-x) | 2019-07-01 |
Prostate | 18 | | 10 | | 3 | Dixon | 2D | GAN\* | def | | | 68Ga-PSMA | 2.4±0.5 | SSIM SUV | [Pozaruk2020](https://doi.org/10.1007/s00259-020-04816-9) | 2020-05-11 | 
Head | 35 | | | 5 | 3 | 3D T1 GRE mDixon+UTEc | 2.5D | U-net | rig | 11.94±0.01 | .87±.03b | 11C-PiB 18F-MK-6240 | <2% | | [Gong2020](https://doi.org/10.1007/s00259-020-05061-w) | 2020-10-27 |
Head | 32 | | | 4 | 3 | Dixon | 3D patch | GAN\* | def | 16±2% | .74±.05b | 18F-FDG| -1.0±13 | SUV | [Gong2020](https://doi.org/10.1109/TRPMS.2020.3006844) | 2020-07-03 | 
Thorax| 14 | | | LoO | 3 | Dixon | 2D | GAN\* | No def | 68±10 | |18F-NaF | | PSNR SSIM RMSE | [Baydoun2020](https://doi.org/10.1016/j.ibmed.2020.100010) | 2020-12 | 
| |
Body | 100 | | 28 | PET, no att corrected | 2D | U-net | Yi | 111±16 | .94±.01b | 18F-FDG | -0.6±2.0% | abs err | [Liu2018](https://doi.org/10.1186/s40658-018-0225-8) |2018-11-12 | 
Body | 100 | | 25 | PET, no att corrected | 2.5D | GAN | Yi | | | 18F-FDG | -0.8±8.6% | SUV ME | [Armanious2020](https://doi.org/10.1186/s13550-020-00644-y0) | 2020-05-24 | 
Body | 80 | | 39 | PET, no att corrected | 3D | GAN | Yi | 109±19 | .87±.03b | 18F-FDG| 0.1<3.0% | NCC PSNR ME | [Dong2019](https://doi.org/10.1088/1361-6560/ab4eb7) | 2019-11-4 |

**Super/subscripts** 
\*comparison with other architecture has been provided; ain air or bowel gas; bin the bony structures; sin the soft tissue; f in the fatty tissue; w in water; jexpressed in terms of Jaccard index and not DSC; iintrinsically registered: PET-CT data; pdata from another MRI sequence used as pre-training; c multiple combinations (also ± Dixon reconstruction, where present) of the sequences were investigated but omitted;
**Abbreviations** 
H&N=head and neck ; val=validation; x-fold=cross-fold ;conf=configuration; arch=architecture; GRE=gradient echo; (T)SE=(turbo) spin-echo, mDixon = multi-contrast Dixon reconstruction; LoO=leave-one-out; (R)MSE=(root) meas squared error; ME=mean error; DSC=dice score coefficient; (N)CC=normalized cross correlation; paed=paediatric

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