Recently the image-to-image translation has experienced significant levels of interest within medical research, beginning with the successful use of the Generative Adversarial Network (GAN) to the introduction of cyclic constraint extended to multiple domains. However, in current approaches, there is no...
In a clinical setting, the acquisition of certain medical image modality is often unavailable due to various considerations such as cost, radiation, etc. Therefore, unpaired cross-modality translation techniques, which involve training on the unpaired data and synthesizing the target modality with the ...
[12]. Zhu, J.Y., Park, T., Isola, P., Efros, A.A.: Unpaired image-to-image translation us- ing cycle-consistent adversarial networks. arXiv preprint arXiv:1703.10593 (2017)
UVCGAN: UNet Vision Transformer cycle-consistent GAN for unpaired image-to-image translation supplementary material 1. Extended UVCGAN Ablation Studies This appendix shows the impact of the UVC- GAN generator, gradient penalty (GP), and self- supervised generator pretraining (PT) on UVC- ...
In2I : Unsupervised Multi-Image-to-Image Translation Using Generative Adversarial Networks In unsupervised image-to-image translation, the goal is to learn the mapping between an input image and an output image using a set of unpaired training im... P Perera,M Abavisani,VM Patel 被引量: 4...
Pathological transition metal deposition and attendant OS constitute an important pathway for cellular dysfunction and death (and hence a potential therapeutic target) in a host of human neurological (Table 1) and medical disorders, and may contribute to the senescence-dependant decline in cognition ...
Recently image-to-image translation has attracted significant interests in\nthe literature, starting from the successful use of the generative adversarial\nnetwork (GAN), to the introduction of cyclic constraint, to extensions to\nmultiple domains. However, in existing approaches, there is no ...
Medical image translation has the potential to reduce the imaging workload, by removing the need to capture some sequences, and to reduce the annotation burden for developing machine learning methods. GANs have been used successfully to translate images from one domain to another, such as MR to...
This study introduces a novel structure-preserving diffusion model specifically designed for unpaired medical image translation, leveraging edge information to represent common anatomical structures across different modalities. To bridge the domain gap effectively, we further propose a novel Interleaved Sampling...
Image translationSegmentationIn the medical domain, the lack of large training data sets and benchmarks is often a limiting factor for training deep neural networks. In contrast to expensive manual labeling, computer simulations...doi:10.1007/978-3-030-32254-0_14Pfeiffer, Micha...