A systematic review of generative artificial intelligence techniques for synthetic medical image datasets: Quality, models, public availability and applications
- DOI
- 10.1016/j.cmpb.2026.109331
- Published
- 2026-06
- Container
- Computer Methods and Programs in Biomedicine
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.cmpb.2026.109331,
title = {A systematic review of generative artificial intelligence techniques for synthetic medical image datasets: Quality, models, public availability and applications},
author = {Xingyue Fu and Xiaoshuang Li and Eduardo Delamare and Adam G. Dunn and Lei Bi and Jinman Kim},
year = {2026},
journal = {Computer Methods and Programs in Biomedicine},
doi = {10.1016/j.cmpb.2026.109331},
url = {https://doi.org/10.1016/j.cmpb.2026.109331}
}RIS
TY - JOUR TI - A systematic review of generative artificial intelligence techniques for synthetic medical image datasets: Quality, models, public availability and applications AU - Xingyue Fu AU - Xiaoshuang Li AU - Eduardo Delamare AU - Adam G. Dunn AU - Lei Bi AU - Jinman Kim PY - 2026 JO - Computer Methods and Programs in Biomedicine DO - 10.1016/j.cmpb.2026.109331 UR - https://doi.org/10.1016/j.cmpb.2026.109331 ER -
APA
Fu, X., Li, X., Delamare, E., Dunn, A. G., Bi, L., & Kim, J. (2026). A systematic review of generative artificial intelligence techniques for synthetic medical image datasets: Quality, models, public availability and applications. Computer Methods and Programs in Biomedicine. https://doi.org/10.1016/j.cmpb.2026.109331
Source records
- crossref · retrieved 2026-09-27T13:07:57.491Z