Source-free cross-modality medical image synthesis with diffusion priors Article Swipe
Jia Chen
,
Xin Wang
,
Jun Bai
,
Kai Yang
,
Xinrong Hu
,
Li Yue
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1007/s44443-025-00200-5
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1007/s44443-025-00200-5
Cross-modality medical image synthesis plays a critical role in enabling comprehensive multi-modal diagnosis and treatment. However, existing methods are constrained by their reliance on paired or unpaired source-target data, limiting scalability and practical deployment. Generating high-fidelity medical images in a truly source-free setting, where no source-domain data is accessible, remains a significant and underexplored challenge. To fill this gap, we propose Diffusion Prior Synthesis and Optimization (DPSO), a novel source-free, diffusion-based framework that performs cross-modality medical image synthesis using only single-modality target data, without requiring supervision or statistical priors from the source domain. DPSO adopts a decoupled architecture via a Probability Flow ODE (PF-ODE) formulation that separates source encoding from target generation. A general-domain diffusion model maps notional source images into a shared latent space, independent of source-domain supervision. This latent representation is then decoded into the target modality using a PF-ODE solver guided by a target-specific prior. An additional optimization stage, also driven by the target prior, further refines the outputs to enhance fidelity and robustness. Experiments on the IXI Dataset and SynthRAD2023 demonstrate that DPSO achieves competitive performance across diverse cross-modality tasks, comparable to methods using paired or unpaired source data. Notably, DPSO removes the need for source modality data entirely, offering a flexible and scalable solution for truly source-free cross-modality medical image synthesis. Code is available at: https://anonymous.4open.science/r/DPSO-64DF
Related Topics
Concepts
No concepts available.
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s44443-025-00200-5
- https://link.springer.com/content/pdf/10.1007/s44443-025-00200-5.pdf
- OA Status
- gold
- References
- 57
- OpenAlex ID
- https://openalex.org/W4414475609
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4414475609Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1007/s44443-025-00200-5Digital Object Identifier
- Title
-
Source-free cross-modality medical image synthesis with diffusion priorsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-09-24Full publication date if available
- Authors
-
Jia Chen, Xin Wang, Jun Bai, Kai Yang, Xinrong Hu, Li YueList of authors in order
- Landing page
-
https://doi.org/10.1007/s44443-025-00200-5Publisher landing page
- PDF URL
-
https://link.springer.com/content/pdf/10.1007/s44443-025-00200-5.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://link.springer.com/content/pdf/10.1007/s44443-025-00200-5.pdfDirect OA link when available
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
57Number of works referenced by this work
Full payload
| id | https://openalex.org/W4414475609 |
|---|---|
| doi | https://doi.org/10.1007/s44443-025-00200-5 |
| ids.doi | https://doi.org/10.1007/s44443-025-00200-5 |
| ids.openalex | https://openalex.org/W4414475609 |
| fwci | 0.0 |
| type | article |
| title | Source-free cross-modality medical image synthesis with diffusion priors |
| biblio.issue | 8 |
| biblio.volume | 37 |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10052 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9976000189781189 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1707 |
| topics[0].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[0].display_name | Medical Image Segmentation Techniques |
| topics[1].id | https://openalex.org/T10824 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9954000115394592 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1707 |
| topics[1].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[1].display_name | Image Retrieval and Classification Techniques |
| topics[2].id | https://openalex.org/T13114 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9921000003814697 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2214 |
| topics[2].subfield.display_name | Media Technology |
| topics[2].display_name | Image Processing Techniques and Applications |
| is_xpac | False |
| apc_list.value | 1350 |
| apc_list.currency | USD |
| apc_list.value_usd | 1350 |
| apc_paid.value | 1350 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 1350 |
| language | en |
| locations[0].id | doi:10.1007/s44443-025-00200-5 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2764955546 |
| locations[0].source.issn | 1319-1578, 2213-1248 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1319-1578 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Journal of King Saud University - Computer and Information Sciences |
| locations[0].source.host_organization | https://openalex.org/P4310320990 |
| locations[0].source.host_organization_name | Elsevier BV |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320990 |
| locations[0].license | cc-by-nc-nd |
| locations[0].pdf_url | https://link.springer.com/content/pdf/10.1007/s44443-025-00200-5.pdf |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by-nc-nd |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Journal of King Saud University Computer and Information Sciences |
| locations[0].landing_page_url | https://doi.org/10.1007/s44443-025-00200-5 |
| locations[1].id | pmh:oai:doaj.org/article:3b44575902e54872b8bfcabc2bb56b59 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306401280 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].source.host_organization_lineage | |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | Journal of King Saud University: Computer and Information Sciences, Vol 37, Iss 8, Pp 1-44 (2025) |
| locations[1].landing_page_url | https://doaj.org/article/3b44575902e54872b8bfcabc2bb56b59 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5101842637 |
| authorships[0].author.orcid | https://orcid.org/0009-0004-7383-488X |
| authorships[0].author.display_name | Jia Chen |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Jia Chen |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5100327844 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-8639-3818 |
| authorships[1].author.display_name | Xin Wang |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Xin Wang |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5064391180 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-3349-5161 |
| authorships[2].author.display_name | Jun Bai |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Jun Bai |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5074866068 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-1982-4398 |
| authorships[3].author.display_name | Kai Yang |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Kai Yang |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5107398424 |
| authorships[4].author.orcid | |
| authorships[4].author.display_name | Xinrong Hu |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Xinrong Hu |
| authorships[4].is_corresponding | False |
| authorships[5].author.id | https://openalex.org/A5100735348 |
| authorships[5].author.orcid | https://orcid.org/0000-0003-3103-0213 |
| authorships[5].author.display_name | Li Yue |
| authorships[5].author_position | last |
| authorships[5].raw_author_name | Yue Li |
| authorships[5].is_corresponding | False |
| has_content.pdf | True |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://link.springer.com/content/pdf/10.1007/s44443-025-00200-5.pdf |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Source-free cross-modality medical image synthesis with diffusion priors |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10052 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9976000189781189 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1707 |
| primary_topic.subfield.display_name | Computer Vision and Pattern Recognition |
| primary_topic.display_name | Medical Image Segmentation Techniques |
| cited_by_count | 0 |
| locations_count | 2 |
| best_oa_location.id | doi:10.1007/s44443-025-00200-5 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2764955546 |
| best_oa_location.source.issn | 1319-1578, 2213-1248 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1319-1578 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Journal of King Saud University - Computer and Information Sciences |
| best_oa_location.source.host_organization | https://openalex.org/P4310320990 |
| best_oa_location.source.host_organization_name | Elsevier BV |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320990 |
| best_oa_location.license | cc-by-nc-nd |
| best_oa_location.pdf_url | https://link.springer.com/content/pdf/10.1007/s44443-025-00200-5.pdf |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Journal of King Saud University Computer and Information Sciences |
| best_oa_location.landing_page_url | https://doi.org/10.1007/s44443-025-00200-5 |
| primary_location.id | doi:10.1007/s44443-025-00200-5 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2764955546 |
| primary_location.source.issn | 1319-1578, 2213-1248 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1319-1578 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Journal of King Saud University - Computer and Information Sciences |
| primary_location.source.host_organization | https://openalex.org/P4310320990 |
| primary_location.source.host_organization_name | Elsevier BV |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320990 |
| primary_location.license | cc-by-nc-nd |
| primary_location.pdf_url | https://link.springer.com/content/pdf/10.1007/s44443-025-00200-5.pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Journal of King Saud University Computer and Information Sciences |
| primary_location.landing_page_url | https://doi.org/10.1007/s44443-025-00200-5 |
| publication_date | 2025-09-24 |
| publication_year | 2025 |
| referenced_works | https://openalex.org/W3120795547, https://openalex.org/W4412978908, https://openalex.org/W2521443754, https://openalex.org/W4309915768, https://openalex.org/W2767044624, https://openalex.org/W2979847946, https://openalex.org/W3121691266, https://openalex.org/W2461164258, https://openalex.org/W2761299546, https://openalex.org/W3176466780, https://openalex.org/W2108598243, https://openalex.org/W3096831136, https://openalex.org/W3130794141, https://openalex.org/W2962784654, https://openalex.org/W4386012666, https://openalex.org/W3122057554, https://openalex.org/W4367848957, https://openalex.org/W3134976640, https://openalex.org/W4387211424, https://openalex.org/W3080245421, https://openalex.org/W2574952845, https://openalex.org/W3033511014, https://openalex.org/W3015328626, https://openalex.org/W3011368758, https://openalex.org/W4223918756, https://openalex.org/W4387757480, https://openalex.org/W2521701804, https://openalex.org/W4353094144, https://openalex.org/W2102166818, https://openalex.org/W4382372079, https://openalex.org/W4401694694, https://openalex.org/W2523123632, https://openalex.org/W2523213734, https://openalex.org/W4379599290, https://openalex.org/W2133665775, https://openalex.org/W3094336018, https://openalex.org/W4385827789, https://openalex.org/W4379619631, https://openalex.org/W4393305452, https://openalex.org/W4402704610, https://openalex.org/W3037260676, https://openalex.org/W3048439504, https://openalex.org/W4388484342, https://openalex.org/W2914057844, https://openalex.org/W3003860948, https://openalex.org/W3132541979, https://openalex.org/W2963163163, https://openalex.org/W3093394156, https://openalex.org/W2962785568, https://openalex.org/W4402780116, https://openalex.org/W3159178846, https://openalex.org/W3007486523, https://openalex.org/W3074741277, https://openalex.org/W2998240002, https://openalex.org/W2962793481, https://openalex.org/W3134475970, https://openalex.org/W3111166321 |
| referenced_works_count | 57 |
| abstract_inverted_index.A | 113 |
| abstract_inverted_index.a | 6, 40, 51, 68, 96, 100, 122, 141, 146, 205 |
| abstract_inverted_index.An | 149 |
| abstract_inverted_index.To | 56 |
| abstract_inverted_index.by | 21, 145, 155 |
| abstract_inverted_index.in | 9, 39 |
| abstract_inverted_index.is | 48, 133, 218 |
| abstract_inverted_index.no | 45 |
| abstract_inverted_index.of | 127 |
| abstract_inverted_index.on | 24, 169 |
| abstract_inverted_index.or | 26, 87, 190 |
| abstract_inverted_index.to | 163, 186 |
| abstract_inverted_index.we | 60 |
| abstract_inverted_index.IXI | 171 |
| abstract_inverted_index.ODE | 103 |
| abstract_inverted_index.and | 14, 32, 53, 65, 166, 173, 207 |
| abstract_inverted_index.are | 19 |
| abstract_inverted_index.at: | 220 |
| abstract_inverted_index.for | 199, 210 |
| abstract_inverted_index.the | 91, 137, 156, 161, 170, 197 |
| abstract_inverted_index.via | 99 |
| abstract_inverted_index.Code | 217 |
| abstract_inverted_index.DPSO | 94, 177, 195 |
| abstract_inverted_index.Flow | 102 |
| abstract_inverted_index.This | 130 |
| abstract_inverted_index.also | 153 |
| abstract_inverted_index.data | 47, 202 |
| abstract_inverted_index.fill | 57 |
| abstract_inverted_index.from | 90, 110 |
| abstract_inverted_index.gap, | 59 |
| abstract_inverted_index.into | 121, 136 |
| abstract_inverted_index.maps | 117 |
| abstract_inverted_index.need | 198 |
| abstract_inverted_index.only | 80 |
| abstract_inverted_index.role | 8 |
| abstract_inverted_index.that | 73, 106, 176 |
| abstract_inverted_index.then | 134 |
| abstract_inverted_index.this | 58 |
| abstract_inverted_index.Prior | 63 |
| abstract_inverted_index.data, | 29, 83 |
| abstract_inverted_index.data. | 193 |
| abstract_inverted_index.image | 3, 77, 215 |
| abstract_inverted_index.model | 116 |
| abstract_inverted_index.novel | 69 |
| abstract_inverted_index.plays | 5 |
| abstract_inverted_index.their | 22 |
| abstract_inverted_index.truly | 41, 211 |
| abstract_inverted_index.using | 79, 140, 188 |
| abstract_inverted_index.where | 44 |
| abstract_inverted_index.PF-ODE | 142 |
| abstract_inverted_index.across | 181 |
| abstract_inverted_index.adopts | 95 |
| abstract_inverted_index.driven | 154 |
| abstract_inverted_index.guided | 144 |
| abstract_inverted_index.images | 38, 120 |
| abstract_inverted_index.latent | 124, 131 |
| abstract_inverted_index.paired | 25, 189 |
| abstract_inverted_index.prior, | 158 |
| abstract_inverted_index.prior. | 148 |
| abstract_inverted_index.priors | 89 |
| abstract_inverted_index.shared | 123 |
| abstract_inverted_index.solver | 143 |
| abstract_inverted_index.source | 92, 108, 119, 192, 200 |
| abstract_inverted_index.space, | 125 |
| abstract_inverted_index.stage, | 152 |
| abstract_inverted_index.target | 82, 111, 138, 157 |
| abstract_inverted_index.tasks, | 184 |
| abstract_inverted_index.(DPSO), | 67 |
| abstract_inverted_index.Dataset | 172 |
| abstract_inverted_index.decoded | 135 |
| abstract_inverted_index.diverse | 182 |
| abstract_inverted_index.domain. | 93 |
| abstract_inverted_index.enhance | 164 |
| abstract_inverted_index.further | 159 |
| abstract_inverted_index.medical | 2, 37, 76, 214 |
| abstract_inverted_index.methods | 18, 187 |
| abstract_inverted_index.outputs | 162 |
| abstract_inverted_index.propose | 61 |
| abstract_inverted_index.refines | 160 |
| abstract_inverted_index.remains | 50 |
| abstract_inverted_index.removes | 196 |
| abstract_inverted_index.without | 84 |
| abstract_inverted_index.(PF-ODE) | 104 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.However, | 16 |
| abstract_inverted_index.Notably, | 194 |
| abstract_inverted_index.achieves | 178 |
| abstract_inverted_index.critical | 7 |
| abstract_inverted_index.enabling | 10 |
| abstract_inverted_index.encoding | 109 |
| abstract_inverted_index.existing | 17 |
| abstract_inverted_index.fidelity | 165 |
| abstract_inverted_index.flexible | 206 |
| abstract_inverted_index.limiting | 30 |
| abstract_inverted_index.modality | 139, 201 |
| abstract_inverted_index.notional | 118 |
| abstract_inverted_index.offering | 204 |
| abstract_inverted_index.performs | 74 |
| abstract_inverted_index.reliance | 23 |
| abstract_inverted_index.scalable | 208 |
| abstract_inverted_index.setting, | 43 |
| abstract_inverted_index.solution | 209 |
| abstract_inverted_index.unpaired | 27, 191 |
| abstract_inverted_index.Diffusion | 62 |
| abstract_inverted_index.Synthesis | 64 |
| abstract_inverted_index.available | 219 |
| abstract_inverted_index.decoupled | 97 |
| abstract_inverted_index.diagnosis | 13 |
| abstract_inverted_index.diffusion | 115 |
| abstract_inverted_index.entirely, | 203 |
| abstract_inverted_index.framework | 72 |
| abstract_inverted_index.practical | 33 |
| abstract_inverted_index.requiring | 85 |
| abstract_inverted_index.separates | 107 |
| abstract_inverted_index.synthesis | 4, 78 |
| abstract_inverted_index.Generating | 35 |
| abstract_inverted_index.additional | 150 |
| abstract_inverted_index.challenge. | 55 |
| abstract_inverted_index.comparable | 185 |
| abstract_inverted_index.synthesis. | 216 |
| abstract_inverted_index.treatment. | 15 |
| abstract_inverted_index.Experiments | 168 |
| abstract_inverted_index.Probability | 101 |
| abstract_inverted_index.accessible, | 49 |
| abstract_inverted_index.competitive | 179 |
| abstract_inverted_index.constrained | 20 |
| abstract_inverted_index.demonstrate | 175 |
| abstract_inverted_index.deployment. | 34 |
| abstract_inverted_index.formulation | 105 |
| abstract_inverted_index.generation. | 112 |
| abstract_inverted_index.independent | 126 |
| abstract_inverted_index.multi-modal | 12 |
| abstract_inverted_index.performance | 180 |
| abstract_inverted_index.robustness. | 167 |
| abstract_inverted_index.scalability | 31 |
| abstract_inverted_index.significant | 52 |
| abstract_inverted_index.source-free | 42, 212 |
| abstract_inverted_index.statistical | 88 |
| abstract_inverted_index.supervision | 86 |
| abstract_inverted_index.Optimization | 66 |
| abstract_inverted_index.SynthRAD2023 | 174 |
| abstract_inverted_index.architecture | 98 |
| abstract_inverted_index.optimization | 151 |
| abstract_inverted_index.source-free, | 70 |
| abstract_inverted_index.supervision. | 129 |
| abstract_inverted_index.comprehensive | 11 |
| abstract_inverted_index.high-fidelity | 36 |
| abstract_inverted_index.source-domain | 46, 128 |
| abstract_inverted_index.source-target | 28 |
| abstract_inverted_index.underexplored | 54 |
| abstract_inverted_index.Cross-modality | 1 |
| abstract_inverted_index.cross-modality | 75, 183, 213 |
| abstract_inverted_index.general-domain | 114 |
| abstract_inverted_index.representation | 132 |
| abstract_inverted_index.diffusion-based | 71 |
| abstract_inverted_index.single-modality | 81 |
| abstract_inverted_index.target-specific | 147 |
| abstract_inverted_index.https://anonymous.4open.science/r/DPSO-64DF | 221 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.47815699 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |