Can deep learning improve image quality of low-dose CT: a prospective study in interstitial lung disease
Author:
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s00330-022-08870-9.pdf
Reference38 articles.
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3. Niemann T, Zbinden I, Roser HW et al (2013) Computed tomography for pulmonary embolism: assessment of a 1-year cohort and estimated cancer risk associated with diagnostic irradiation. Acta Radiol 54(7):778–784
4. Ohno Y, Yaguchi A, Okazaki T et al (2016) Comparative evaluation of newly developed model-based and commercially available hybrid-type iterative reconstruction methods and filter back projection method in terms of accuracy of computer-aided volumetry (CADv) for low-dose CT protocols in phantom study. Eur J Radiol 85(8):1375–1382
5. Laqmani A, Regier M, Veldhoen S et al (2014) Improved image quality and low radiation dose with hybrid iterative reconstruction with 80 kV CT pulmonary angiography. Eur J Radiol 83(10):1962–1969
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