Spinal Apophyses Localization in Discretized Models of Human Backs by Shape Index Analysis
The proposed inexpensive and easy-to-use approach significantly advances over other non-invasive methods. Its ability to detect the apophyses' location potentially offers new capabilities in detecting, diagnosing, and monitoring spinal disorders.
Authors
- Paolo Di Stefano (ORCID: https://orcid.org/0000-0001-5003-2084)
- Emanuele Guardiani (ORCID: https://orcid.org/0000-0002-1623-1474)
- Luca Di Angelo (ORCID: https://orcid.org/0000-0002-5341-0500)
- Anna Eva Morabito (ORCID: https://orcid.org/0000-0001-8841-5558)
Institutions
- University of Salento (IT)
- University of L'Aquila (IT)
- Innovation Engineering (Italy) (IT)
Publication Details
- Journal
- IEEE Transactions on Biomedical Engineering
- Published
- 2024-08-15
- DOI
- https://doi.org/10.1109/tbme.2024.3414674
- Citations
- 1
- Primary Topic
- Medical Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.18
Funders
- Ministero dell’Istruzione, dell’Università e della Ricerca