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Digital Molecular Magnetic Resonance Imaging

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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Hlavní autoři: Awojoyogbe, Bamidele O. (Autor), Dada, Michael O. (Autor)
Korporativní autor: SpringerLink (Online service)
Médium: Elektronický zdroj E-kniha
Jazyk:angličtina
Vydáno: Singapore : Springer Nature Singapore : Imprint: Springer, 2024.
Vydání:1st ed. 2024.
Edice:Series in BioEngineering,
Témata:
Nuclear magnetic resonance.
Biomedical engineering.
Machine learning.
Cancer > Imaging.
Neural networks (Computer science) .
Biophysics.
Magnetic Resonance (NMR, EPR).
Biomedical Engineering and Bioengineering.
Machine Learning.
Cancer Imaging.
Mathematical Models of Cognitive Processes and Neural Networks.
Bioanalysis and Bioimaging.
On-line přístup:https://doi.org/10.1007/978-981-97-6370-2
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Obsah:
  • General Introduction
  • Physics Informed Neural Networks PINNS
  • New Methodology and Modelling In Magnetic Resonance Imaging
  • Physics informed Neural Network for Addressing Spatial and Temporal
  • Machine Learning Model for Diagnosis of Pulmonary Arterial Hypertension
  • A Convolution Neural Network for Artificial Intelligence-Based Classification of Alzheimer’s Diseases
  • Physics informed Neural Networks for Nuclear Magnetic Resonance Guided Clinical Hyperthermia.

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