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pro vyhledávání: '"Bedel, Hasan A"'
Autor:
Mirza, Muhammad U., Dalmaz, Onat, Bedel, Hasan A., Elmas, Gokberk, Korkmaz, Yilmaz, Gungor, Alper, Dar, Salman UH, Çukur, Tolga
Deep generative models have gained recent traction in accelerated MRI reconstruction. Diffusion priors are particularly promising given their representational fidelity. Instead of the target transformation from undersampled to fully-sampled data requ
Externí odkaz:
http://arxiv.org/abs/2308.01096
Autor:
Bedel, Hasan Atakan, Çukur, Tolga
Deep learning analyses have offered sensitivity leaps in detection of cognitive states from functional MRI (fMRI) measurements across the brain. Yet, as deep models perform hierarchical nonlinear transformations on their input, interpreting the assoc
Externí odkaz:
http://arxiv.org/abs/2307.09547
Learning-based methods have recently enabled performance leaps in analysis of high-dimensional functional MRI (fMRI) time series. Deep learning models that receive as input functional connectivity (FC) features among brain regions have been commonly
Externí odkaz:
http://arxiv.org/abs/2301.00439
Autor:
Özbey, Muzaffer, Dalmaz, Onat, Dar, Salman UH, Bedel, Hasan A, Özturk, Şaban, Güngör, Alper, Çukur, Tolga
Imputation of missing images via source-to-target modality translation can improve diversity in medical imaging protocols. A pervasive approach for synthesizing target images involves one-shot mapping through generative adversarial networks (GAN). Ye
Externí odkaz:
http://arxiv.org/abs/2207.08208
Deep-learning models have enabled performance leaps in analysis of high-dimensional functional MRI (fMRI) data. Yet, many previous methods are suboptimally sensitive for contextual representations across diverse time scales. Here, we present BolT, a
Externí odkaz:
http://arxiv.org/abs/2205.11578
Autor:
Güngör, Alper, Dar, Salman UH, Öztürk, Şaban, Korkmaz, Yilmaz, Bedel, Hasan A., Elmas, Gokberk, Ozbey, Muzaffer, Çukur, Tolga
Publikováno v:
In Medical Image Analysis August 2023 88
Publikováno v:
In Medical Image Analysis August 2023 88
Akademický článek
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Akademický článek
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Publikováno v:
Signal Processing and Communications Applications Conference (SIU)
Conference Name: 2022 30th Signal Processing and Communications Applications Conference (SIU) Date of Conference: 15-18 May 2022 Functional magnetic resonance imaging (fMRI) enables recording the brain’s neural activity spatiotemporally and is the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a9fbe7a62efefe3363df06c7af9316e
https://hdl.handle.net/11693/111296
https://hdl.handle.net/11693/111296