Deep Learning for Radiographic Measurement of Femoral Component Subsidence Following Total Hip Arthroplasty-Reference-Cited by-同舟云学术

Deep Learning for Radiographic Measurement of Femoral Component Subsidence Following Total Hip Arthroplasty

Published:2022-05-01 Issue:3 Volume:4 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Rouzrokh Pouria¹^ORCID,Wyles Cody C.¹^ORCID,Kurian Shyam J.¹^ORCID,Ramazanian Taghi¹^ORCID,Cai Jason C.¹^ORCID,Huang Qiao¹^ORCID,Zhang Kuan¹^ORCID,Taunton Michael J.¹,Maradit Kremers Hilal¹^ORCID,Erickson Bradley J.¹^ORCID

Affiliation:

1. From the Department of Radiology, Radiology Informatics Laboratory (P.R., J.C.C., Q.H., K.Z., B.J.E.), Department of Health Sciences Research (C.C.W., T.R., M.J.T., H.M.K.), Department of Orthopedic Surgery (C.C.W., T.R., M.J.T., H.M.K.), Department of Clinical Anatomy (C.C.W.), and Mayo Clinic Alix School of Medicine (S.J.K.), Mayo Clinic, 200 First St SW, Rochester, MN 55905.

Funder

Mayo Foundation Presidential Fund

National Institutes of Health

Publisher

Radiological Society of North America (RSNA)

Subject

Artificial Intelligence,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.210206

Reference10 articles.

1. Total hip arthroplasty

2. Why Revision Total Hip Arthroplasty Fails