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Abstract #5176

Protocol for in vivo acquisition and fully-automated segmentation of the anterior cruciate ligament

Laura Bernadette Lane1, Gabriel della Maggiora1,2, Nicolás Schlotterbeck1, Cristián Montalba1, Pablo Besa3, Sebastián Irarrazaval3, Alvaro Burdiles4, and Pablo Irarrazaval1,2,5

1Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile, 2Department of Electrical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, 3Department of Orthopedics and Traumatology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile, 4Department of Radiology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile, 5Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile

In this preclinical study we propose a protocol for rapid 3D imaging and fully automated segmentation to create a standardized healthy ACL image database. The segmentation problem of the ACL is particularly challenging due to its poor contrast. Our protocol demonstrated promising fully-automated segmentation of the ACL. Thus, allowing us to have a 3D computational model of the ACL. Ongoing experimentation explores dynamic imaging of the ACL in motions of flexion-extension. Such work will improve understanding of in vivo knee mechanics with potential to inform treatment of different injuries related to the ACL.

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