Browsing by Keywords "Generative"
Now showing items 1-7 of 7
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Deep MRI reconstruction with generative vision transformer
(Springer, 2021)Supervised training of deep network models for MRI reconstruction requires access to large databases of fully-sampled MRI acquisitions. To alleviate dependency on costly databases, unsupervised learning strategies have ... -
Deep unsupervised learning for accelerated MRI reconstruction
(Bilkent University, 2022-07)Supervised reconstruction models are characteristically trained on matched pairs of undersampled and fully-sampled data to capture an MRI prior, along with supervision regarding the imaging operator to enforce data ... -
edaGAN: Encoder-Decoder Attention Generative Adversarial Networks for multi-contrast MR image synthesis
(Institute of Electrical and Electronics Engineers, 2022-05-16)Magnetic resonance imaging (MRI) is the preferred modality among radiologists in the clinic due to its superior depiction of tissue contrast. Its ability to capture different contrasts within an exam session allows it to ... -
Federated learning of generative ımage priors for MRI reconstruction
(Institute of Electrical and Electronics Engineers Inc., 2022-11-09)Multi-institutional efforts can facilitate training of deep MRI reconstruction models, albeit privacy risks arise during cross-site sharing of imaging data. Federated learning (FL) has recently been introduced to address ... -
MRI reconstruction with conditional adversarial transformers
(Springer Cham, 2022-09-22)Deep learning has been successfully adopted for accelerated MRI reconstruction given its exceptional performance in inverse problems. Deep reconstruction models are commonly based on convolutional neural network (CNN) ... -
ResViT: residual vision transformers for multimodal medical ımage synthesis
(Institute of Electrical and Electronics Engineers Inc., 2022-04-18)Generative adversarial models with convolutional neural network (CNN) backbones have recently been established as state-of-the-art in numerous medical image synthesis tasks. However, CNNs are designed to perform local ... -
Unsupervised MRI reconstruction via zero-shot learned adversarial transformers
(Institute of Electrical and Electronics Engineers Inc., 2022-01-27)Supervised reconstruction models are characteristically trained on matched pairs of undersampled and fully-sampled data to capture an MRI prior, along with supervision regarding the imaging operator to enforce data ...
