000 03897nam a22006255i 4500
001 978-981-97-6370-2
003 DE-He213
005 20251030112912.0
007 cr nn 008mamaa
008 240825s2024 si | s |||| 0|eng d
020 _a9789819763702
_9978-981-97-6370-2
024 7 _a10.1007/978-981-97-6370-2
_2doi
050 4 _aQC762
072 7 _aPNFR
_2bicssc
072 7 _aSCI074000
_2bisacsh
072 7 _aPNFR
_2thema
100 1 _aAwojoyogbe, Bamidele O.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_982882
245 1 0 _aDigital Molecular Magnetic Resonance Imaging
_h[electronic resource] /
_cby Bamidele O. Awojoyogbe, Michael O. Dada.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXXV, 348 p. 171 illus., 134 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSeries in BioEngineering,
_x2196-887X
505 0 _aGeneral 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.
520 _aThis 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 been possible for researchers and clinicians. The computational and digital algorithms developed can enable a more thorough understanding of the intricate structures found within the human body, surpassing the constraints of traditional 2D methods. The Physics-informed Neural Networks as presented can enhance three-dimensional rendering for deeper understanding of the spatial relationships and subtle abnormalities of anatomical features and sets the stage for upcoming advancements that could impact a wider range of digital heath modalities. This book opens the door to ultra-powerful digital molecular MRI powered by quantum computing that can perform calculations that would take supercomputers millions of years.
650 0 _aNuclear magnetic resonance.
_982883
650 0 _aBiomedical engineering.
650 0 _aMachine learning.
_955059
650 0 _aCancer
_xImaging.
_969161
650 0 _aNeural networks (Computer science) .
_964231
650 0 _aBiophysics.
_966239
650 1 4 _aMagnetic Resonance (NMR, EPR).
_982884
650 2 4 _aBiomedical Engineering and Bioengineering.
650 2 4 _aMachine Learning.
_955059
650 2 4 _aCancer Imaging.
_969163
650 2 4 _aMathematical Models of Cognitive Processes and Neural Networks.
_965860
650 2 4 _aBioanalysis and Bioimaging.
_968565
700 1 _aDada, Michael O.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_982885
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819763696
776 0 8 _iPrinted edition:
_z9789819763719
776 0 8 _iPrinted edition:
_z9789819763726
830 0 _aSeries in BioEngineering,
_x2196-887X
_973546
856 4 0 _uhttps://doi.org/10.1007/978-981-97-6370-2
912 _aZDB-2-PHA
912 _aZDB-2-SXP
999 _c62733
_d62733