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Paired Diffusion: Generation of related, synthetic PET-CT-Segmentation scans using Linked Denoising Diffusion Probabilistic Models
March 27, 2024, 4:46 a.m. | Rowan Bradbury, Katherine A. Vallis, Bartlomiej W. Papiez
cs.CV updates on arXiv.org arxiv.org
Abstract: The rapid advancement of Artificial Intelligence (AI) in biomedical imaging and radiotherapy is hindered by the limited availability of large imaging data repositories. With recent research and improvements in denoising diffusion probabilistic models (DDPM), high quality synthetic medical scans are now possible. Despite this, there is currently no way of generating multiple related images, such as a corresponding ground truth which can be used to train models, so synthetic scans are often manually annotated before …
abstract advancement artificial artificial intelligence arxiv availability biomedical cs.cv data ddpm denoising diffusion eess.iv imaging improvements intelligence medical pet quality repositories research scans segmentation synthetic type
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