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  • 1
    Online-Ressource
    Online-Ressource
    Cham :Springer International Publishing :
    UID:
    almahu_9949115155602882
    Umfang: XXXI, 389 p. 117 illus., 109 illus. in color. , online resource.
    Ausgabe: 1st ed. 2021.
    ISBN: 9783030767280
    Serie: Biological and Medical Physics, Biomedical Engineering,
    Inhalt: Based on the analytical methods and the computer programs presented in this book, all that may be needed to perform MRI tissue diagnosis is the availability of relaxometric data and simple computer program proficiency. These programs are easy to use, highly interactive and the data processing is fast and unambiguous. Laboratories (with or without sophisticated facilities) can perform computational magnetic resonance diagnosis with only T1 and T2 relaxation data. The results have motivated the use of data to produce data-driven predictions required for machine learning, artificial intelligence (AI) and deep learning for multidisciplinary and interdisciplinary research. Consequently, this book is intended to be very useful for students, scientists, engineers, the medial personnel and researchers who are interested in developing new concepts for deeper appreciation of computational magnetic Resonance Imaging for medical diagnosis, prognosis, therapy and management of tissue diseases.
    Anmerkung: Chapter 1. General Introduction -- Chapter 2. Fundamental Of Nmr -- Chapter 3. Computational Diffusion Magnetic Resonance Imaging -- Chapter 4. Radiofrequency Identification (Rfid) System For Computational Magnetic Resonance Imaging Of Blood Flow At Suction Points -- Chapter 5. A Computational Magnetic Resonance Imaging Based On Bloch Nmr Flow Equation, Mri Finger Printing, Python Deep Learning For The Classification Of Adult Brain Tumours -- Chapter 6. Analysis Of Hydrogen-Like Ions For Neurocomputing Based On Bloch Nmr Flow Equation -- Chapter 7. Quantum Mechanical Model Of Bloch Nmr Flow Equations For The Transport Analysis Of Quantm-Drugs In Microscopic Blood Vessels Applicable In Nanomedicine -- Chapter 8. Application Of "R" Machine Learning For Magnetic Resonance Relaxometry Data-Representation And Classification Of Human Brain Tumours -- Chapter 9. Advanced Magnetic Resonance Image Processing And Quantitative Analysis In Avizo For Demonstrating Radiomic Contrast Between Radiation Necrosis And Tumor Progression -- Chapter 10. Computational Analysis of Magnetic Resonance Imaging Contrast Agents and their Physico-Chemical Variables -- Chapter 11. General Conclusion.
    In: Springer Nature eBook
    Weitere Ausg.: Printed edition: ISBN 9783030767273
    Weitere Ausg.: Printed edition: ISBN 9783030767297
    Weitere Ausg.: Printed edition: ISBN 9783030767303
    Sprache: Englisch
    URL: Volltext  (URL des Erstveröffentlichers)
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 2
    UID:
    gbv_1765220475
    Umfang: 1 Online-Ressource (XXXI, 389 Seiten)
    ISBN: 9783030767280
    Serie: Biological and medical physics, biomedical engineering
    Inhalt: Based on the analytical methods and the computer programs presented in this book, all that may be needed to perform MRI tissue diagnosis is the availability of relaxometric data and simple computer program proficiency. These programs are easy to use, highly interactive and the data processing is fast and unambiguous. Laboratories (with or without sophisticated facilities) can perform computational magnetic resonance diagnosis with only T1 and T2 relaxation data. The results have motivated the use of data to produce data-driven predictions required for machine learning, artificial intelligence (AI) and deep learning for multidisciplinary and interdisciplinary research. Consequently, this book is intended to be very useful for students, scientists, engineers, the medial personnel and researchers who are interested in developing new concepts for deeper appreciation of computational magnetic Resonance Imaging for medical diagnosis, prognosis, therapy and management of tissue diseases.
    Anmerkung: Chapter 1. General Introduction -- Chapter 2. Fundamental Of Nmr -- Chapter 3. Computational Diffusion Magnetic Resonance Imaging -- Chapter 4. Radiofrequency Identification (Rfid) System For Computational Magnetic Resonance Imaging Of Blood Flow At Suction Points -- Chapter 5. A Computational Magnetic Resonance Imaging Based On Bloch Nmr Flow Equation, Mri Finger Printing, Python Deep Learning For The Classification Of Adult Brain Tumours -- Chapter 6. Analysis Of Hydrogen-Like Ions For Neurocomputing Based On Bloch Nmr Flow Equation -- Chapter 7. Quantum Mechanical Model Of Bloch Nmr Flow Equations For The Transport Analysis Of Quantm-Drugs In Microscopic Blood Vessels Applicable In Nanomedicine -- Chapter 8. Application Of “R” Machine Learning For Magnetic Resonance Relaxometry Data-Representation And Classification Of Human Brain Tumours -- Chapter 9. Advanced Magnetic Resonance Image Processing And Quantitative Analysis In Avizo For Demonstrating Radiomic Contrast Between Radiation Necrosis And Tumor Progression -- Chapter 10. Computational Analysis of Magnetic Resonance Imaging Contrast Agents and their Physico-Chemical Variables -- Chapter 11. General Conclusion.
    Weitere Ausg.: ISBN 9783030767273
    Weitere Ausg.: ISBN 9783030767297
    Weitere Ausg.: ISBN 9783030767303
    Weitere Ausg.: Erscheint auch als Druck-Ausgabe Dada, Michael O. Computational molecular magnetic resonance imaging for neuro-oncology Cham, Switzerland : Springer, 2021 ISBN 3030767272
    Weitere Ausg.: ISBN 9783030767273
    Sprache: Englisch
    Fachgebiete: Medizin
    RVK:
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 3
    Online-Ressource
    Online-Ressource
    Cham, Switzerland :Springer,
    UID:
    edoccha_9959950632202883
    Umfang: 1 online resource (412 pages)
    ISBN: 3-030-76728-0
    Serie: Biological and Medical Physics, Biomedical Engineering
    Weitere Ausg.: ISBN 3-030-76727-2
    Sprache: Englisch
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 4
    Online-Ressource
    Online-Ressource
    Cham, Switzerland :Springer,
    UID:
    almafu_9959950632202883
    Umfang: 1 online resource (412 pages)
    ISBN: 3-030-76728-0
    Serie: Biological and Medical Physics, Biomedical Engineering
    Weitere Ausg.: ISBN 3-030-76727-2
    Sprache: Englisch
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
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