Digital Molecular Magnetic Resonance Imaging

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Éditeur :

Springer

Paru le : 2024-08-24

This book pushes the limits of conventional MRI visualization methods by completely changing the medical imaging landscape and leads to innovations that will help patients and healthcare providers alike. It enhances the capabilities of MRI anatomical visualization to a level that has never before be...
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Éditeur

Collection
n.c

Parution
2024-08-24

Pages
348 pages

EAN papier
9789819763696

Dr. Awojoyogbe O. B. has Ph.D. (1997) in Med. Phy. from Federal University of Technology Nigeria in collaboration with Institute of Biomed. Eng. & Med. Informatics, ETH Zurich & Univ. of Zurich. He won the 2003 Young African Math. Medal Award by African Mathematical Union. He is a professor of Physics and associate member of International Center for Theoretical Physics (ICTP), Trieste, Italy. His research field is Theory, Dynamics & Applications of Magnetic Resonance Imaging. He is a researcher of the Centre for Vaccine & Drug Development at the Federal University of Technology Minna. He served as the deputy director, Academic Planning (2008–2011) and the director, Academic Planning (2011–2015) at his University. His current research interests are the application of computational molecular magnetic resonance imaging for digital health, Quantum Artificial Intelligence (QAI)-and in particular, its subset research area Quantum Machine Learning (QML). Dr. Dada O. M. received his B.Tech. (Physics/Electronics with First class honours) from the Fed. Univ. of Tech., Minna, Nigeria in 2006, M.Tech. (Solid State Physics) and Ph.D. (Physics) from the same university in 2010 and 2016, respectively, under the supervision of Professor O.B. Awojoyogbe. He currently holds an academic position as a senior lecturer in the Dept. of Physics of the University. He has been involved in magnetic resonance modeling of biological systems and applications of computational molecular magnetic resonance imaging for digital health, Quantum Artificial Intelligence (QAI)-and in particular, its subset research area Quantum Machine Learning (QML).

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EAN PDF
9789819763702
Prix
168,79 €
Nombre pages copiables
3
Nombre pages imprimables
34
Taille du fichier
24781 Ko
EAN EPUB
9789819763702
Prix
168,79 €
Nombre pages copiables
3
Nombre pages imprimables
34
Taille du fichier
67533 Ko

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