Artificial Intelligence/Machine Learning in Nuclear Medicine
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-00119-2_9
Reference59 articles.
1. Staffaroni AM, Elahi FM, McDermott D, Marton K, Karageorgiou E, Sacco S, et al. Neuroimaging in dementia. Semin Neurol. 2017;37(5):510–37. https://doi.org/10.1055/s-0037-1608808.
2. Nasrallah I, Dubroff J. An overview of PET neuroimaging. Semin Nucl Med. 2013;43(6):449–61. https://doi.org/10.1053/j.semnuclmed.2013.06.003.
3. Friston KJ, Frith CD, Liddle PF, Frackowiak RS. Comparing functional (PET) images: the assessment of significant change. J Cereb Blood Flow Metab. 1991;11(4):690–9. https://doi.org/10.1038/jcbfm.1991.122.
4. Friston KJ, Frith CD, Liddle PF, Dolan RJ, Lammertsma AA, Frackowiak RS. The relationship between global and local changes in PET scans. J Cereb Blood Flow Metab. 1990;10(4):458–66. https://doi.org/10.1038/jcbfm.1990.88.
5. Nestor PJ, Altomare D, Festari C, Drzezga A, Rivolta J, Walker Z, et al. Clinical utility of FDG-PET for the differential diagnosis among the main forms of dementia. Eur J Nucl Med Mol Imaging. 2018;45(9):1509–25. https://doi.org/10.1007/s00259-018-4035-y.
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