Generating Scoliotic Computed Tomography Volumes from Finite Element Spine Models-Reference-Cited by-同舟云学术

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Generating Scoliotic Computed Tomography Volumes from Finite Element Spine Models

Published:2022 Issue: Volume: Page:91-103
ISSN:
Container-title:Computational Biomechanics for Medicine
language:
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Author:

Tapp Austin,Polanco Michael,Kumi Isaac,Bawab Sebastian,Ringleb Stacie,Kakar Rumit,Remy Carl St.,Bennett James,Audette Michel

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-09327-2_6

Reference32 articles.

1. Shen, D., Wu, G., & Suk, H. (2017). Deep learning in medical image analysis. Annual Review of Biomedical Engineering, 19, 221–248.

2. Ibragimov, B., Korez, R., et al. (2017). Segmentation of pathological structures by landmark-assisted deformable models. IEEE Transactions on Medical Imaging, 36(7), 1457–1469.

3. Mongan, J., Moy, L., & Kahn, C. E. (2020). Checklist for artificial intelligence in medical imaging (CLAIM): A guide for authors and reviewers. Radiology: Artificial Intelligence, 2(2).

4. Illés, T., & Somoskeöy, S. (2012) The EOSTM imaging system and its uses in daily orthopaedic practice. International orthopaedics. Springer.

5. Mohamed, M., Trivedi, J., et al. (2020). Adolescent idiopathic scoliosis: A review of current concepts. Orthopaedics and Trauma, 34(6), 338–345.

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