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Autor:
Kyambikwa Bisangamo, C.1 cele.kyambis@gmail.fcom, Mulongo Mbarambara, Ph.1, Kalakuko Kyetile, E.1, Wakeka Kabyuma, Cl.1, Kapepa Ngoli, J.2
Publikováno v:
Technologies de Laboratoire. 2014, Vol. 8 Issue 36, p22-28. 7p.
Autor:
Randle, Christopher P.
Publikováno v:
Castanea, 2017 Sep 01. 82(2), 174-175.
Externí odkaz:
https://www.jstor.org/stable/26353921
The anisotropic structure of the myocardium is a key determinant of the cardiac function. To date, there is no imaging modality to assess in-vivo the cardiac fiber structure. We recently proposed Fibernet, a method for the automatic identification of
Externí odkaz:
http://arxiv.org/abs/2410.23388
Precision cardiology based on cardiac digital twins requires accurate simulations of cardiac arrhythmias. However, detailed models, such as the monodomain model, are computationally costly and have limited applicability in practice. Thus, it desirabl
Externí odkaz:
http://arxiv.org/abs/2410.22583
Autor:
Aristoteles1 calvinaristo@yahoo.co.id, Shatriadi, Heri1, Zairinayati1, Haryoko, Imam1, Poddar, Sandeep2
Publikováno v:
Malaysian Journal of Medicine & Health Sciences. 2021 Supplement 4, p7-10. 4p.
Autor:
GIVHAN, ROBIN
Publikováno v:
Newsweek. 9/26/2011, Vol. 158 Issue 13, p44-47. 4p. 2 Color Photographs, 1 Black and White Photograph.
Recent works have shown that traditional Neural Network (NN) architectures display a marked frequency bias in the learning process. Namely, the NN first learns the low-frequency features before learning the high-frequency ones. In this study, we rigo
Externí odkaz:
http://arxiv.org/abs/2405.14957
Autor:
Molina, Juan, Bousse, Alexandre, Catalán, Tabita, Wang, Zhihan, Petrache, Mircea, Sahli, Francisco, Prieto, Claudia, Courdurier, Matìas
Magnetic resonance imaging (MRI) is fundamental for the assessment of many diseases, due to its excellent tissue contrast characterization. This is based on quantitative techniques, such as T1 , T2 , and T2* mapping. Quantitative MRI requires the acq
Externí odkaz:
http://arxiv.org/abs/2404.18182
Autor:
Spieker, Veronika, Eichhorn, Hannah, Stelter, Jonathan K., Huang, Wenqi, Braren, Rickmer F., Rückert, Daniel, Costabal, Francisco Sahli, Hammernik, Kerstin, Prieto, Claudia, Karampinos, Dimitrios C., Schnabel, Julia A.
Neural implicit k-space representations have shown promising results for dynamic MRI at high temporal resolutions. Yet, their exclusive training in k-space limits the application of common image regularization methods to improve the final reconstruct
Externí odkaz:
http://arxiv.org/abs/2404.08350