| Autor: |
Becker Anna Maria, Schaufelberger Matthias, Kühle Reinald Peter, Freudlsperger Christian, Nahm Werner |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Current Directions in Biomedical Engineering, Vol 9, Iss 1, Pp 198-201 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2364-5504 |
| DOI: |
10.1515/cdbme-2023-1050 |
| Popis: |
Introduction: 3D surface scan-based diagnosis of craniosynostosis is a promising radiation-free alternative to traditional diagnosis using computed tomography. The cranial index (CI) and the cranial vault asymmetry index (CVAI) are well-established clinical parameters that are widely used. However, they also have the benefit of being easily adaptable for automatic diagnosis without the need of extensive preprocessing. Methods: We propose a multi-height-based classification approach that uses CI and CVAI in different height layers and compare it to the initial approach using only one layer. We use ten-fold cross-validation and test seven different classifiers. The dataset of 504 patients consists of three types of craniosynostosis and a control group consisting of healthy and non-synostotic subjects. Results: The multi-height-based approach improved classification for all classifiers. The k-nearest neighbors classifier scored best with a mean accuracy of 89% and a mean F1-score of 0.75. Conclusion: Taking height into account is beneficial for the classification. Based on accepted and widely used clinical parameters, this might be a step towards an easy-to-understand and transparent classification approach for both physicians and patients. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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