| 000 | 04024naaaa2201033uu 4500 | ||
|---|---|---|---|
| 001 | https://directory.doabooks.org/handle/20.500.12854/76914 | ||
| 005 | 20220220043107.0 | ||
| 020 | _abooks978-3-0365-2109-1 | ||
| 020 | _a9783036521107 | ||
| 020 | _a9783036521091 | ||
| 024 | 7 |
_a10.3390/books978-3-0365-2109-1 _cdoi |
|
| 041 | 0 | _aEnglish | |
| 042 | _adc | ||
| 072 | 7 |
_aM _2bicssc |
|
| 100 | 1 |
_ade Jong, Pim A. _4edt |
|
| 700 | 1 |
_aFoppen, Wouter _4edt |
|
| 700 | 1 |
_aTolboom, Nelleke _4edt |
|
| 700 | 1 |
_ade Jong, Pim A. _4oth |
|
| 700 | 1 |
_aFoppen, Wouter _4oth |
|
| 700 | 1 |
_aTolboom, Nelleke _4oth |
|
| 245 | 1 | 0 | _aSystems Radiology and Personalized Medicine |
| 260 |
_aBasel, Switzerland _bMDPI - Multidisciplinary Digital Publishing Institute _c2021 |
||
| 300 | _a1 electronic resource (180 p.) | ||
| 506 | 0 |
_aOpen Access _2star _fUnrestricted online access |
|
| 520 | _aMedicine has evolved into a high level of specialization using the very detailed imaging of organs. This has impressively solved a multitude of acute health-related problems linked to single-organ diseases. Many diseases and pathophysiological processes, however, involve more than one organ. An organ-based approach is challenging when considering disease prevention and caring for elderly patients, or those with systemic chronic diseases or multiple co-morbidities. In addition, medical imaging provides more than a pretty picture. Much of the data are now revealed by quantitating algorithms with or without artificial intelligence. This Special Issue on “Systems Radiology and Personalized Medicine” includes reviews and original studies that show the strengths and weaknesses of structural and functional whole-body imaging for personalized medicine. | ||
| 540 |
_aCreative Commons _fhttps://creativecommons.org/licenses/by/4.0/ _2cc _4https://creativecommons.org/licenses/by/4.0/ |
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| 546 | _aEnglish | ||
| 650 | 7 |
_aMedicine _2bicssc |
|
| 653 | _aCOVID-19 | ||
| 653 | _achest X-ray | ||
| 653 | _adeep learning | ||
| 653 | _aconvolutional neural network | ||
| 653 | _aGrad-CAM | ||
| 653 | _acomputed tomography | ||
| 653 | _aimage analysis | ||
| 653 | _aosteoarthritis | ||
| 653 | _areliability | ||
| 653 | _aFDG-PET/CT | ||
| 653 | _ainfection | ||
| 653 | _abloodstream infection | ||
| 653 | _aendocarditis | ||
| 653 | _avascular graft infection | ||
| 653 | _aspondylodiscitis | ||
| 653 | _acyst infection | ||
| 653 | _awhite blood cell scintigraphy | ||
| 653 | _atotal body PET/CT | ||
| 653 | _aradiotracers | ||
| 653 | _aartificial intelligence | ||
| 653 | _acontrast media | ||
| 653 | _abody composition | ||
| 653 | _alarge vessel vasculitis | ||
| 653 | _aatherosclerosis | ||
| 653 | _aimaging | ||
| 653 | _aFDG-PET | ||
| 653 | _aradiological imaging | ||
| 653 | _aMRI | ||
| 653 | _anon-contrast | ||
| 653 | _avenography | ||
| 653 | _aTRANCE | ||
| 653 | _aQFlow | ||
| 653 | _aneuroblastoma | ||
| 653 | _anuclear medicine | ||
| 653 | _aradionuclide imaging | ||
| 653 | _a[123I]mIBG | ||
| 653 | _a[124I]mIBG | ||
| 653 | _a[18F]mFBG | ||
| 653 | _a[18F]FDG | ||
| 653 | _a[68Ga]Ga-DOTA peptides | ||
| 653 | _a[18F]F-DOPA | ||
| 653 | _a[11C]mHED | ||
| 653 | _achronic limb-threatening ischemia | ||
| 653 | _aperipheral arterial disease | ||
| 653 | _acalcification pattern | ||
| 653 | _adiffuse idiopathic skeletal hyperostosis | ||
| 653 | _arisk factors | ||
| 653 | _aadiposity | ||
| 653 | _aintra-abdominal fat | ||
| 653 | _acardiorenal syndrome | ||
| 653 | _aimaging biomarker | ||
| 653 | _atissue characterization | ||
| 653 | _acerebral aneurysm | ||
| 653 | _acomputational fluid dynamics | ||
| 653 | _ahemodynamic | ||
| 653 | _amorphological | ||
| 653 | _arupture | ||
| 653 | _an/a | ||
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://mdpi.com/books/pdfview/book/4384 _70 _zDOAB: download the publication |
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://directory.doabooks.org/handle/20.500.12854/76914 _70 _zDOAB: description of the publication |
| 999 |
_c65222 _d65222 |
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