Name
Abstract | ||
|---|---|---|
It is often necessary to register partial objects in medical imaging. Due to limited field of view (FOV), the entirety of an object cannot always be imaged. This study presents a novel application of an existing registration algorithm to this problem. The spin-image algorithm [1] creates pose-invariant representations of global shape with respect to individual mesh vertices. These 'spin-images,' are then compared for two different poses of the same object to establish correspondences and subsequently determine relative orientation of the poses. In this study, the spin-image algorithm is applied to 4DCT-derived capitate bone surfaces to assess the relative accuracy of registration with various amounts of geometry excluded. The limited longitudinal coverage under the 4DCT technique (38.4mm, [2]), results in partial views of the capitate when imaging wrist motions. This study assesses the ability of the spin-image algorithm to register partial bone surfaces by artificially restricting the capitate geometry available for registration. Under IRB approval, standard static CT and 4DCT scans were obtained on a patient. The capitate was segmented from the static CT and one phase of 4DCT in which the whole bone was available. Spin-image registration was performed between the static and 4DCT. Distal portions of the 4DCT capitate (10-70%) were then progressively removed and registration was repeated. Registration accuracy was evaluated by angular errors and the percentage of sub-resolution fitting. It was determined that 60% of the distal capitate could be omitted without appreciable effect on registration accuracy using the spin-image algorithm (angular error < 1.5 degree, sub-resolution fitting > 98.4%). |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1117/12.2008685 | Proceedings of SPIE |
Keywords | Field | DocType |
spin image,hidden point removal,registration,partial object,4DCT,wrist | Field of view,Capitate bone,Computer vision,Spin-½,Wrist,Vertex (geometry),Medical imaging,Angular error,IRB Approval,Artificial intelligence,Physics | Conference |
Volume | ISSN | Citations |
8671 | 0277-786X | 1 |
PageRank | References | Authors |
0.36 | 3 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| ryan breighner | 1 | 1 | 0.70 |
| David R Holmes | 2 | 42 | 20.31 |
| Shuai Leng | 3 | 14 | 2.88 |
| Kai-Nan An | 4 | 9 | 3.68 |
| Cynthia H. McCollough | 5 | 6 | 2.95 |
| kristin zhao | 6 | 1 | 0.70 |