Learning to detect anatomical landmarks of the pelvis in X-rays from arbitrary views-Reference-Cited by-同舟云学术

Learning to detect anatomical landmarks of the pelvis in X-rays from arbitrary views

Published:2019-04-20 Issue:9 Volume:14 Page:1463-1473
ISSN:1861-6410
Container-title:International Journal of Computer Assisted Radiology and Surgery
language:en
Short-container-title:Int J CARS

Author:

Bier Bastian,Goldmann Florian,Zaech Jan-Nico,Fotouhi Javad,Hegeman Rachel,Grupp Robert,Armand Mehran,Osgood Greg,Navab Nassir,Maier Andreas,Unberath Mathias

Funder

National Institutes of Health

Nvidia

Publisher

Springer Science and Business Media LLC

Subject

Health Informatics,Radiology, Nuclear Medicine and imaging,General Medicine,Surgery,Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition,Biomedical Engineering

Link

http://link.springer.com/content/pdf/10.1007/s11548-019-01975-5.pdf

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4. Bier B, Unberath M, Zaech JN, Fotouhi J, Armand M, Osgood G, Navab N, Maier A (2018) X-ray-transform invariant anatomical landmark detection for pelvic trauma surgery. In: International conference on medical image computing and computer-assisted intervention. Springer, New York, pp 55–63

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