Inferring 3D finger bone shapes from 2D images – a detailed analysis of shape accuracy
| Autor: | Anna Rörich, Annkristin Lange, Stefan Heldmann, Jan H. Moltz, Lars Walczak, Sinef Yarar-Schlickewei, Felix Güttler, Joachim Georgii |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, Vol 12, Iss 1 (2024) |
| Druh dokumentu: | article |
| ISSN: | 21681163 2168-1171 2168-1163 |
| DOI: | 10.1080/21681163.2024.2359397 |
| Popis: | 3D visualisation and modelling of anatomical structures of the human body play a significant role in diagnosis, computer-aided surgery, surgical planning, and patient follow-up. However, 2D X-ray images are often used in clinical routine. We propose and validate a method for reconstructing 3D shapes from 2D X-ray scans. This method comprises automatic segmentation and labelling, automated construction of 3D statistical shape models (SSM), and automatic fitting of the SSM to standard 2D X-ray images. This workflow is applied to finger bone shape reconstruction and validated for each finger bone using a set of five synthetic reference configurations and 34 CT/X-ray data pairs. We reached submillimetre accuracy for 91.59% of the synthetic data, while 79.65% of the clinical cases show surface errors below 2 mm. Thus, applying the proposed method can add valuable 3D information where 3D imaging is not indicated. Moreover, 3D imaging can be avoided if the 2D-3D reconstruction accuracy is sufficient. |
| Databáze: | Directory of Open Access Journals |
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