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- research-articleFebruary 2024
Few-shot biomedical image segmentation using diffusion models: Beyond image generation
- Bardia Khosravi,
- Pouria Rouzrokh,
- John P. Mickley,
- Shahriar Faghani,
- Kellen Mulford,
- Linjun Yang,
- A. Noelle Larson,
- Benjamin M. Howe,
- Bradley J. Erickson,
- Michael J. Taunton,
- Cody C. Wyles
Computer Methods and Programs in Biomedicine (CBIO), Volume 242, Issue Chttps://doi.org/10.1016/j.cmpb.2023.107832Highlights- Diffusion models create realistic radiographs that are not discernable by experts.
- Synthetic images can be reliably conditioned on demographic and radiologic attributes.
- DDPMs can be used for meaningful feature extraction from ...
Medical image analysis pipelines often involve segmentation, which requires a large amount of annotated training data, which is time-consuming and costly. To address this issue, we proposed leveraging generative models to achieve few-...