Abstracts tagged "Deep Learning"

Abstract Number: 1474 • ACR Convergence 2021
Automatic Detection of Bone Marrow Lesions from Knee MRI Data from the OAI Study
Shen Liu¹, Xiaoxiao Sun¹, Frank Roemer², Erin Ashbeck³, Edward Bedrick¹, Zong-Ming Li¹, Ali Guermazi⁴ and Kent Kwoh¹, ¹University of Arizona, Tucson, AZ, ²Friedrich-Alexander University Erlangen-Nurnberg, Erlangen, Germany, ³University of Arizona Arthritis Center, Tucson, AZ, ⁴Boston University, Boston, MA
Background/Purpose: Subchondral bone marrow lesions (BMLs) are associated with symptoms and structural progression of knee OA. BMLs are characterized by diffuse hyperintensity on fat suppressed…

All abstracts accepted to ACR Convergence are under media embargo once the ACR has notified presenters of their abstract’s acceptance. They may be presented at other meetings or published as manuscripts after this time but should not be discussed in non-scholarly venues or outlets. The following embargo policies are strictly enforced by the ACR.

Accepted abstracts are made available to the public online in advance of the meeting and are published in a special online supplement of our scientific journal, Arthritis & Rheumatology. Information contained in those abstracts may not be released until the abstracts appear online. In an exception to the media embargo, academic institutions, private organizations, and companies with products whose value may be influenced by information contained in an abstract may issue a press release to coincide with the availability of an ACR abstract on the ACR website. However, the ACR continues to require that information that goes beyond that contained in the abstract (e.g., discussion of the abstract done as part of editorial news coverage) is under media embargo until 10:00 AM ET on November 14, 2024. Journalists with access to embargoed information cannot release articles or editorial news coverage before this time. Editorial news coverage is considered original articles/videos developed by employed journalists to report facts, commentary, and subject matter expert quotes in a narrative form using a variety of sources (e.g., research, announcements, press releases, events, etc.).

Violation of this policy may result in the abstract being withdrawn from the meeting and other measures deemed appropriate. Authors are responsible for notifying colleagues, institutions, communications firms, and all other stakeholders related to the development or promotion of the abstract about this policy. If you have questions about the ACR abstract embargo policy, please contact ACR abstracts staff at [email protected].

Abstracts tagged "Deep Learning"

Automatic Detection of Bone Marrow Lesions from Knee MRI Data from the OAI Study