Pulli B, Heit JJ, Wintermark M (2021) Computed tomography–based imaging algorithms for patient selection in acute ischemic stroke. Neuroimaging Clin N Am 31:235–250
Arndt C, Güttler F, Heinrich A, Bürckenmeyer F, Diamantis I, Teichgräber U (2021) Deep learning CT image reconstruction in clinical practice. RöFo - Fortschritte auf dem gebiet der Röntgenstrahlen und der bildgebenden Verfahren 193:252–261
Qiu D, Seeram E (2016) Does iterative reconstruction improve image quality and reduce dose in computed tomography?? Radiol Open J 1:42–54
Heinrich A, Streckenbach F, Beller E, Groß J, Weber M-A, Meinel FG (2021) Deep learning-based image reconstruction for CT angiography of the aorta. Diagnostics 11:2037
CAS PubMed PubMed Central Google Scholar
Qu T, Guo Y, Li J et al (2022) Iterative reconstruction vs deep learning image reconstruction: comparison of image quality and diagnostic accuracy of arterial stenosis in low-dose lower extremity CT angiography. Br J Radiol 95(1140):20220196
Singh S, Kalra MK, Hsieh J et al (2010) Abdominal CT: comparison of adaptive statistical iterative and filtered back projection reconstruction techniques. Radiology 257:373–383
Southard RN, Bardo DME, Temkit MH, Thorkelson MA, Augustyn RA, Martinot CA (2019) Comparison of iterative model reconstruction versus filtered back-projection in pediatric emergency head CT: dose, image quality, and image-reconstruction times. AJNR Am J Neuroradiol 40:866–871
CAS PubMed PubMed Central Google Scholar
Steuwe A, Boeven J, Cordes L et al (2021) Impact of increasing levels of adaptive statistical iterative reconstruction on image quality in oil-based postmortem CT angiography in coronary arteries. Int J Legal Med 135:1869–1878
PubMed PubMed Central Google Scholar
Guido G, Polici M, Nacci I et al (2023) Iterative reconstruction: State-of-the-Art and future perspectives. J Comput Assist Tomogr 47(2):244–254
Kwon H, Cho J, Oh J et al (2015) The adaptive statistical iterative reconstruction-V technique for radiation dose reduction in abdominal CT: comparison with the adaptive statistical iterative reconstruction technique. Br J Radiol 88:20150463
PubMed PubMed Central Google Scholar
Koetzier LR, Mastrodicasa D, Szczykutowicz TP et al (2023) Deep learning image reconstruction for CT: technical principles and clinical prospects. Radiology 306(3):e221257
Barca P, Giannelli M, Fantacci ME, Caramella D (2018) Computed tomography imaging with the adaptive statistical iterative reconstruction (ASIR) algorithm: dependence of image quality on the blending level of reconstruction. Australas Phys Eng Sci Med 41:463–473
Krol AL, Dzialowski I, Roy J et al (2007) Incidence of radiocontrast nephropathy in patients undergoing acute stroke computed tomography angiography. Stroke 38:2364–2366
Rha J-H, Saver JL (2007) The impact of recanalization on ischemic stroke outcome. Stroke 38:967–973
Kleindorfer DO, Towfighi A, Chaturvedi S et al (2021) 2021 Guideline for the Prevention of Stroke in Patients With Stroke and Transient Ischemic Attack: A Guideline From the American Heart Association/American Stroke Association. Stroke;52
Menon BK, Demchuk AM (2011) Computed tomography angiography in the assessment of patients with stroke/TIA. Neurohospitalist 1:187–199
PubMed PubMed Central Google Scholar
ICRP (2007) Managing patient dose in Multi-Detector Computed Tomography (MDCT). ICRP publication 102. Ann ICRP 37 (1)
Jiang C, Jin D, Liu Z, Zhang Y, Ni M, Yuan H (2022) Deep learning image reconstruction algorithm for carotid dual-energy computed tomography angiography: evaluation of image quality and diagnostic performance. Insights Imaging 13:182
PubMed PubMed Central Google Scholar
Zhang F, Lu Z, Wang F (2020) Advances in the pathogenesis and prevention of contrast-induced nephropathy. Life Sci 259:118379
Mehran R, Dangas GD, Weisbord SD (2019) Contrast-associated acute kidney injury. N Engl J Med 380:2146–2155
Bello HR, Graves JA, Rohatgi S et al (2019) Skull base–related lesions at routine head CT from the emergency department: pearls, pitfalls, and lessons learned. Radiographics 39:1161–1182
Pula M, Kucharczyk E, Zdanowicz A, Guzinski M (2023) Image quality improvement in deep learning image reconstruction of head computed tomography examination. Tomography 9:1485–1493
PubMed PubMed Central Google Scholar
Kim I, Kang H, Yoon HJ, Chung BM, Shin N-Y (2021) Deep learning-based image reconstruction for brain CT: improved image quality compared with adaptive statistical iterative reconstruction-Veo (ASIR-V). Neuroradiology 63:905–912
Sun J, Li H, Wang B et al (2021) Application of a deep learning image reconstruction (DLIR) algorithm in head CT imaging for children to improve image quality and lesion detection. BMC Med Imaging 21:108
PubMed PubMed Central Google Scholar
Lei L, Zhou Y, Guo X et al (2023) The value of a deep learning image reconstruction algorithm in whole-brain computed tomography perfusion in patients with acute ischemic stroke. Quant Imaging Med Surg 13:8173–8189
PubMed PubMed Central Google Scholar
European Comission (2014) Radiation Protection N° 180:Medical Radiation Exposure of the European Population. Luxemburg
Fazel R, Krumholz HM, Wang Y et al (2009) Exposure to low-dose ionizing radiation from medical imaging procedures. N Engl J Med 361:849–857
CAS PubMed PubMed Central Google Scholar
Damilakis J, Hierath M, Clark J et al (2021) Protection N o 195 European study on clinical diagnostic reference levels for X-ray medical imaging
Smith-Bindman R (2009) Radiation dose associated with common computed tomography examinations and the associated lifetime attributable risk of cancer. Arch Intern Med 169:2078
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