Deep learning-enhanced zero echo time MRI for glenohumeral assessment in shoulder instability: a comparative study with CT
DL-based reconstruction enhances ZTE MRI quality for glenohumeral assessment, offering osseous evaluation and quantification equivalent to gold-standard CT, potentially simplifying preoperative workflow, and reducing CT radiation exposure.
Authors
- Elena Rodríguez‐Iñigo (ORCID: https://orcid.org/0000-0003-0454-1333)
- Graeme C. McKinnon (ORCID: https://orcid.org/0000-0001-9195-9492)
- Sagar Mandava (ORCID: https://orcid.org/0000-0003-3425-7579)
- Michael Carl (ORCID: https://orcid.org/0000-0002-9936-5813)
- Florian Wiesinger (ORCID: https://orcid.org/0000-0002-5597-6057)
- Santiago Aráuz (ORCID: https://orcid.org/0000-0002-6357-2431)
- Norberto Malpica (ORCID: https://orcid.org/0000-0003-4618-7459)
- Juan Manuel López‐Alcorocho (ORCID: https://orcid.org/0000-0003-3333-3365)
- Eugenia Sánchez-Lacalle
- Mario Padrón
- J. de Arcos (ORCID: https://orcid.org/0000-0002-1855-4285)
- Satish Nagrani
- Maggie Fung
- Laura Carretero-Gómez (ORCID: https://orcid.org/0009-0007-6998-1045)
Institutions
- Universidad Rey Juan Carlos (ES)
- Clínica Rementería (ES)
- Siemens Healthineers (Germany) (DE)
Publication Details
- Journal
- Skeletal Radiology
- Published
- 2024-11-22
- DOI
- https://doi.org/10.1007/s00256-024-04830-0
- Citations
- 9
- Primary Topic
- Shoulder Injury and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 5.15