Name
Title | ||
|---|---|---|
A kinematics-based method for generating cartilage maps and deformations in the multi-articulating wrist joint from CT images. |
Abstract | ||
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We present a non-invasive method for estimating individual-specific cartilage maps directly from in vivo kine- matic data and computed tomography (CT) volume images, and a novel algorithm for computing cartilage surface deforma- tions. Our proposed cartilage model, a meshless incompressible height-field captures the physical properties important for estimating the shape, contact area, and deformation magnitude of cartilage at each articulation. This cartilage model can serve as an effective building block for a future forward-dynamic predictive model of the human wrist. I. INTRODUCTION The carpal cartilages in the wrist are among the least documented soft-tissue structures in human anatomy, impact- ing negatively our understanding of the many degenerative and repetitive-strain diseases afflicting this versatile joint. The reasons lie in the very versatile nature of the wrist articulation: its complexity and compactness (eight kidney- bean-sized bones) means cartilage is thinner than in other joints. Carpal cartilage is thus hard to image in vivo, although that is where its functional role in wrist kinematics would be most naturally investigated. In turn, examination in vitro requires invasive disruption of the articulation and thus results in artificially-imposed kinematics. We introduce a non-invasive, individual-specific carpal cartilage modeling approach that allows for the in vivo exploration of cartilage functional role. We present a method for estimating individual-specific cartilage maps (location and thickness) directly from in vivo kinematic data and computed tomography (CT) volume images, and a novel algorithm for computing cartilage surface deformations. Our proposed cartilage model, a meshless incompressible height- field captures the physical properties important for estimating the shape, contact area, and deformation magnitude of car- tilage at each articulation. The model is more complex and potentially more realistic than other current in vivo carpal cartilage models (1), while being faster to calculate than finite element approaches (2). Thus our model can serve as an effective building block for a future forward-dynamic predictive model of the human wrist. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/IEMBS.2006.259742 | Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference |
Keywords | DocType | Volume |
biomechanics,computerised tomography,biomedical measurement,ct images,kinematics-based method,in vivo kinematic data,multiarticulating wrist joint,bone,physical properties,deformation,cartilage surface deformation,kinematics,computed tomography volume images,cartilage map estimation | Conference | 1 |
ISSN | ISBN | Citations |
1557-170X | 1-4244-003303 | 1 |
PageRank | References | Authors |
0.44 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| G Elisabeta Marai | 1 | 136 | 20.43 |
| Joseph J. Crisco | 2 | 95 | 10.65 |
| David H. Laidlaw | 3 | 1781 | 234.58 |