Anatomy-centred deep learning improves generalisability and progression prediction in radiographic sacroiliitis detection

Anatomy-centred deep learning improves generalisability and progression prediction in radiographic sacroiliitis detection

Purpose To examine whether incorporating anatomy-centred deep learning can improve generalisability and enable prediction of disease progression.Methods This retrospective multicentre study included conventional pelvic radiographs of four different patient cohorts focusing on axial spondyloarthritis...

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Bibliographic Details
Main Authors: Denis Poddubnyy, Torsten Diekhoff, Lina Xu, Hildrun Haibel, Fabian Proft, Mikhail Protopopov, Valeria Rios Rodriguez, Murat Torgutalp, Judith Rademacher, Kay-Geert Hermann, Marcus R. Makowski, Felix J. Dorfner, Janis L. Vahldiek, Leonhard Donle, Andrei Zhukov, Hartmut Häntze, Hugo J. W. L. Aerts, Lisa C. Adams, Keno K. Bressem
Format: Article
Language:English
Published: BMJ Publishing Group 2024-12-01
Series:RMD Open
Online Access:https://rmdopen.bmj.com/content/10/4/e004628.full

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https://rmdopen.bmj.com/content/10/4/e004628.full

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