Anonymizing Radiographs Using an Object Detection Deep Learning Algorithm-Reference-Cited by-同舟云学术

Anonymizing Radiographs Using an Object Detection Deep Learning Algorithm

Published:2023-11-01 Issue:6 Volume:5 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Khosravi Bardia¹^ORCID,Mickley John P.¹^ORCID,Rouzrokh Pouria¹^ORCID,Taunton Michael J.¹^ORCID,Larson A. Noelle¹,Erickson Bradley J.¹^ORCID,Wyles Cody C.¹^ORCID

Affiliation:

1. From the Orthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery (B.K., J.P.M., P.R., M.J.T., A.N.L., C.C.W.), Radiology Informatics Laboratory, Department of Radiology (B.K., P.R., B.J.E.), Department of Orthopedic Surgery (M.J.T., A.N.L., C.C.W.), and Department of Clinical Anatomy (C.C.W.), Mayo Clinic, 200 1st St SW, Rochester, MN 55905.

Funder

Mayo Foundation Presidential Fund

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.230085

Reference13 articles.

1. A clinical audit of anatomical side marker use in a paediatric medical imaging department

2. Institute of Medicine · Board on Health Care Services · Board on Health Sciences Policy · Committee on Health Research and the Privacy of Health Information: The HIPAA Privacy Rule. Beyond the HIPAA Privacy Rule: Enhancing Privacy, Improving Health Through Research. National Academies Press; 2009. https://play.google.com/store/books/details?id=jUGcAgAAQBAJ. Accessed February 1, 2023.

3. A DICOM dataset for evaluation of medical image de-identification

4. Deep learning predicts hip fracture using confounding patient and healthcare variables

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