Federated Pseudo Modality Generation for Incomplete Multi-Modal MRI Reconstruction Article Swipe
Yunlu Yan
,
Chun-Mei Feng
,
Yuexiang Li
,
Rick Siow Mong Goh
,
Lei Zhu
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2308.10910
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2308.10910
While multi-modal learning has been widely used for MRI reconstruction, it relies on paired multi-modal data which is difficult to acquire in real clinical scenarios. Especially in the federated setting, the common situation is that several medical institutions only have single-modal data, termed the modality missing issue. Therefore, it is infeasible to deploy a standard federated learning framework in such conditions. In this paper, we propose a novel communication-efficient federated learning framework, namely Fed-PMG, to address the missing modality challenge in federated multi-modal MRI reconstruction. Specifically, we utilize a pseudo modality generation mechanism to recover the missing modality for each single-modal client by sharing the distribution information of the amplitude spectrum in frequency space. However, the step of sharing the original amplitude spectrum leads to heavy communication costs. To reduce the communication cost, we introduce a clustering scheme to project the set of amplitude spectrum into finite cluster centroids, and share them among the clients. With such an elaborate design, our approach can effectively complete the missing modality within an acceptable communication cost. Extensive experiments demonstrate that our proposed method can attain similar performance with the ideal scenario, i.e., all clients have the full set of modalities. The source code will be released.
Related Topics
Concepts
Modality (human–computer interaction)
Computer science
Centroid
Modal
Set (abstract data type)
Cluster analysis
Modalities
Code (set theory)
Scheme (mathematics)
Data mining
Data sharing
Artificial intelligence
Missing data
Machine learning
Mathematics
Mathematical analysis
Medicine
Sociology
Polymer chemistry
Alternative medicine
Social science
Chemistry
Programming language
Pathology
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2308.10910
- https://arxiv.org/pdf/2308.10910
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386113756
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4386113756Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2308.10910Digital Object Identifier
- Title
-
Federated Pseudo Modality Generation for Incomplete Multi-Modal MRI ReconstructionWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-08-20Full publication date if available
- Authors
-
Yunlu Yan, Chun-Mei Feng, Yuexiang Li, Rick Siow Mong Goh, Lei ZhuList of authors in order
- Landing page
-
https://arxiv.org/abs/2308.10910Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2308.10910Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2308.10910Direct OA link when available
- Concepts
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Modality (human–computer interaction), Computer science, Centroid, Modal, Set (abstract data type), Cluster analysis, Modalities, Code (set theory), Scheme (mathematics), Data mining, Data sharing, Artificial intelligence, Missing data, Machine learning, Mathematics, Mathematical analysis, Medicine, Sociology, Polymer chemistry, Alternative medicine, Social science, Chemistry, Programming language, PathologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.real | 22 |
| abstract_inverted_index.step | 116 |
| abstract_inverted_index.such | 59, 156 |
| abstract_inverted_index.that | 34, 176 |
| abstract_inverted_index.them | 151 |
| abstract_inverted_index.this | 62 |
| abstract_inverted_index.used | 6 |
| abstract_inverted_index.will | 200 |
| abstract_inverted_index.with | 184 |
| abstract_inverted_index.While | 0 |
| abstract_inverted_index.among | 152 |
| abstract_inverted_index.cost, | 132 |
| abstract_inverted_index.cost. | 172 |
| abstract_inverted_index.data, | 41 |
| abstract_inverted_index.heavy | 125 |
| abstract_inverted_index.i.e., | 188 |
| abstract_inverted_index.ideal | 186 |
| abstract_inverted_index.leads | 123 |
| abstract_inverted_index.novel | 67 |
| abstract_inverted_index.share | 150 |
| abstract_inverted_index.which | 16 |
| abstract_inverted_index.attain | 181 |
| abstract_inverted_index.client | 101 |
| abstract_inverted_index.common | 31 |
| abstract_inverted_index.costs. | 127 |
| abstract_inverted_index.deploy | 52 |
| abstract_inverted_index.finite | 146 |
| abstract_inverted_index.issue. | 46 |
| abstract_inverted_index.method | 179 |
| abstract_inverted_index.namely | 72 |
| abstract_inverted_index.paired | 13 |
| abstract_inverted_index.paper, | 63 |
| abstract_inverted_index.pseudo | 89 |
| abstract_inverted_index.reduce | 129 |
| abstract_inverted_index.relies | 11 |
| abstract_inverted_index.scheme | 137 |
| abstract_inverted_index.source | 198 |
| abstract_inverted_index.space. | 113 |
| abstract_inverted_index.termed | 42 |
| abstract_inverted_index.widely | 5 |
| abstract_inverted_index.within | 168 |
| abstract_inverted_index.acquire | 20 |
| abstract_inverted_index.address | 75 |
| abstract_inverted_index.clients | 190 |
| abstract_inverted_index.cluster | 147 |
| abstract_inverted_index.design, | 159 |
| abstract_inverted_index.medical | 36 |
| abstract_inverted_index.missing | 45, 77, 96, 166 |
| abstract_inverted_index.project | 139 |
| abstract_inverted_index.propose | 65 |
| abstract_inverted_index.recover | 94 |
| abstract_inverted_index.several | 35 |
| abstract_inverted_index.sharing | 103, 118 |
| abstract_inverted_index.similar | 182 |
| abstract_inverted_index.utilize | 87 |
| abstract_inverted_index.Fed-PMG, | 73 |
| abstract_inverted_index.However, | 114 |
| abstract_inverted_index.approach | 161 |
| abstract_inverted_index.clients. | 154 |
| abstract_inverted_index.clinical | 23 |
| abstract_inverted_index.complete | 164 |
| abstract_inverted_index.learning | 2, 56, 70 |
| abstract_inverted_index.modality | 44, 78, 90, 97, 167 |
| abstract_inverted_index.original | 120 |
| abstract_inverted_index.proposed | 178 |
| abstract_inverted_index.setting, | 29 |
| abstract_inverted_index.spectrum | 110, 122, 144 |
| abstract_inverted_index.standard | 54 |
| abstract_inverted_index.Extensive | 173 |
| abstract_inverted_index.amplitude | 109, 121, 143 |
| abstract_inverted_index.challenge | 79 |
| abstract_inverted_index.difficult | 18 |
| abstract_inverted_index.elaborate | 158 |
| abstract_inverted_index.federated | 28, 55, 69, 81 |
| abstract_inverted_index.framework | 57 |
| abstract_inverted_index.frequency | 112 |
| abstract_inverted_index.introduce | 134 |
| abstract_inverted_index.mechanism | 92 |
| abstract_inverted_index.released. | 202 |
| abstract_inverted_index.scenario, | 187 |
| abstract_inverted_index.situation | 32 |
| abstract_inverted_index.Especially | 25 |
| abstract_inverted_index.Therefore, | 47 |
| abstract_inverted_index.acceptable | 170 |
| abstract_inverted_index.centroids, | 148 |
| abstract_inverted_index.clustering | 136 |
| abstract_inverted_index.framework, | 71 |
| abstract_inverted_index.generation | 91 |
| abstract_inverted_index.infeasible | 50 |
| abstract_inverted_index.scenarios. | 24 |
| abstract_inverted_index.conditions. | 60 |
| abstract_inverted_index.demonstrate | 175 |
| abstract_inverted_index.effectively | 163 |
| abstract_inverted_index.experiments | 174 |
| abstract_inverted_index.information | 106 |
| abstract_inverted_index.modalities. | 196 |
| abstract_inverted_index.multi-modal | 1, 14, 82 |
| abstract_inverted_index.performance | 183 |
| abstract_inverted_index.distribution | 105 |
| abstract_inverted_index.institutions | 37 |
| abstract_inverted_index.single-modal | 40, 100 |
| abstract_inverted_index.Specifically, | 85 |
| abstract_inverted_index.communication | 126, 131, 171 |
| abstract_inverted_index.reconstruction, | 9 |
| abstract_inverted_index.reconstruction. | 84 |
| abstract_inverted_index.communication-efficient | 68 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/17 |
| sustainable_development_goals[0].score | 0.47999998927116394 |
| sustainable_development_goals[0].display_name | Partnerships for the goals |
| citation_normalized_percentile |