Name
Abstract | ||
|---|---|---|
The paper discusses the initial results obtained for the generation of canonical 3D models of anatomical parts, built on real patient data. 3D canonical models of anatomy are key elements in a computer-assisted diagnosis; for instance, they can support pathology detection, semantic annotation of patient-specific 3D reconstructions, quantification of pathological markers. Our approach is focused on carpal bones and on the elastic analysis of 3D reconstructions of these bones, which are segmented from MRI scans, represented as 0-genus triangle meshes, and parameterized on the sphere. The original method [8] relies on a set of sparse correspondences, defined as matching vertices. For medical applications, it is desirable to constrain the mean shape generation to set-up the correspondences among a larger set of anatomical landmarks, including vertices, lines, and areas. Preliminary results are discussed and future development directions are sketched. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-23222-5_21 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
Medical data,Carpal bones,Shape analysis,Mean shape | Computer vision,Parameterized complexity,Carpal bones,Polygon mesh,Semantic annotation,Pattern recognition,Vertex (geometry),Computer science,Canonical model,Artificial intelligence,Shape analysis (digital geometry) | Conference |
Volume | ISSN | Citations |
9281 | 0302-9743 | 3 |
PageRank | References | Authors |
0.39 | 8 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Imon Banerjee | 1 | 48 | 11.45 |
| Hamid Laga | 2 | 376 | 27.28 |
| Giuseppe Patanè | 3 | 163 | 17.87 |
| Kurtek, Sebastian | 4 | 246 | 21.52 |
| Anuj Srivastava | 5 | 2853 | 199.47 |
| Michela Spagnuolo | 6 | 1496 | 95.81 |