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pro vyhledávání: '"Hope, Thomas A."'
Autor:
Hope, Thomas M. H., Price, Cathy J., Halai, Ajay, Salvi, Carola, Crinion, Jenny, Keijsers, Merel, Sperber, Christoph, Bowman, Howard
In many scientific disciplines, the features of interest cannot be observed directly, so must instead be inferred from observed behaviour. Latent variable analyses are increasingly employed to systematise these inferences, and Principal Components An
Externí odkaz:
http://arxiv.org/abs/2401.12905
Autor:
White, Adam, Saranti, Margarita, Garcez, Artur d'Avila, Hope, Thomas M. H., Price, Cathy J., Bowman, Howard
Machine learning offers great potential for automated prediction of post-stroke symptoms and their response to rehabilitation. Major challenges for this endeavour include the very high dimensionality of neuroimaging data, the relatively small size of
Externí odkaz:
http://arxiv.org/abs/2310.19174
Autor:
Rajagopal, Abhejit, Westphalen, Antonio C., Velarde, Nathan, Ullrich, Tim, Simko, Jeffry P., Nguyen, Hao, Hope, Thomas A., Larson, Peder E. Z., Magudia, Kirti
Non-invasive prostate cancer detection from MRI has the potential to revolutionize patient care by providing early detection of clinically-significant disease (ISUP grade group >= 2), but has thus far shown limited positive predictive value. To addre
Externí odkaz:
http://arxiv.org/abs/2212.06336
Autor:
Rajagopal, Abhejit, Natsuaki, Yutaka, Wangerin, Kristen, Hamdi, Mahdjoub, An, Hongyu, Sunderland, John J., Laforest, Richard, Kinahan, Paul E., Larson, Peder E. Z., Hope, Thomas A.
Historically, patient datasets have been used to develop and validate various reconstruction algorithms for PET/MRI and PET/CT. To enable such algorithm development, without the need for acquiring hundreds of patient exams, in this paper we demonstra
Externí odkaz:
http://arxiv.org/abs/2206.05618
Autor:
Rajagopal, Abhejit, Leynes, Andrew P., Dwork, Nicholas, Scholey, Jessica E., Hope, Thomas A., Larson, Peder E. Z.
In this paper, we review physics- and data-driven reconstruction techniques for simultaneous positron emission tomography (PET) / magnetic resonance imaging (MRI) systems, which have significant advantages for clinical imaging of cancer, neurological
Externí odkaz:
http://arxiv.org/abs/2206.06788
Autor:
Armstrong, Wesley R., Kishan, Amar U., Booker, Kiara M., Grogan, Tristan R., Elashoff, David, Lam, Ethan C., Clark, Kevyn J., Steinberg, Michael L., Fendler, Wolfgang P., Hope, Thomas A., Nickols, Nicholas G., Czernin, Johannes, Calais, Jeremie
Publikováno v:
In European Urology July 2024 86(1):52-60
Autor:
White, Adam, Saranti, Margarita, d’Avila Garcez, Artur, Hope, Thomas M.H., Price, Cathy J., Bowman, Howard
Publikováno v:
In NeuroImage: Clinical 2024 43
Autor:
Leynes, Andrew P., Ahn, Sangtae P., Wangerin, Kristen A., Kaushik, Sandeep S., Wiesinger, Florian, Hope, Thomas A., Larson, Peder E. Z.
Publikováno v:
IEEE Transactions on Radiation and Plasma Medical Sciences, Early access, 2021
A major remaining challenge for magnetic resonance-based attenuation correction methods (MRAC) is their susceptibility to sources of MRI artifacts (e.g. implants, motion) and uncertainties due to the limitations of MRI contrast (e.g. accurate bone de
Externí odkaz:
http://arxiv.org/abs/2001.03414
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