Automatic pulmonary vessel segmentation on noncontrast chest CT: deep learning algorithm developed using spatiotemporally matched virtual noncontrast images and low-keV contrast-enhanced vessel maps-Reference-Cited by-同舟云学术

Automatic pulmonary vessel segmentation on noncontrast chest CT: deep learning algorithm developed using spatiotemporally matched virtual noncontrast images and low-keV contrast-enhanced vessel maps

Published:2021-05-19 Issue:12 Volume:31 Page:9012-9021
ISSN:0938-7994
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Nam Ju Gang,Witanto Joseph Nathanael,Park Sang Joon,Yoo Seung Jin,Goo Jin Mo,Yoon Soon Ho^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-021-08036-z.pdf

Reference27 articles.

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3. Zhou C, Chan H-P, Hadjiiski LM et al (2006) Automatic pulmonary vessel segmentation in 3D computed tomographic pulmonary angiographic (CTPA) imagesMedical Imaging 2006: Image Processing. International Society for Optics and Photonics, pp 61444Q

4. Kaftan JN, Bakai A, Das M, Aach T (2008) Locally adaptive fuzzy pulmonary vessel segmentation in contrast enhanced CT data2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro. IEEE, pp 101–104

5. Rahaghi FN, Argemí G, Nardelli P et al (2019) Pulmonary vascular density: comparison of findings on computed tomography imaging with histology. Eur Respir J 54:1900370

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