Name
Abstract | ||
|---|---|---|
3D printer applications in the biomedical sciences and medical imaging are expanding and will have an increasing impact on the practice of medicine. Orthopedic and reconstructive surgery has been an obvious area for development of 3D printer applications as the segmentation of bony anatomy to generate printable models is relatively straightforward. There are important issues that should be addressed when using 3D printed models for applications that may affect patient care; in particular the dimensional accuracy of the printed parts needs to be high to avoid poor decisions being made prior to surgery or therapeutic procedures. In this work, the dimensional accuracy of 3D printed vertebral bodies derived from CT data for a cadaver spine is compared with direct measurements on the ex-vivo vertebra and with measurements made on the 3D rendered vertebra using commercial 3D image processing software. The vertebra was printed on a consumer grade 3D printer using an additive print process using PLA (polylactic acid) filament. Measurements were made for 15 different anatomic features of the vertebral body, including vertebral body height, endplate width and depth, pedicle height and width, and spinal canal width and depth, among others. It is shown that for the segmentation and printing process used, the results of measurements made on the 3D printed vertebral body are substantially the same as those produced by direct measurement on the vertebra and measurements made on the 3D rendered vertebra. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1117/12.2043489 | Proceedings of SPIE |
Keywords | Field | DocType |
3D printing,orthopedic modeling,dimensional accuracy,vertebral modeling | 3d printer,Cadaver,Computer vision,Medical imaging,Segmentation,3d image processing,Artificial intelligence,3D printing,Vertebra,Spinal canal,Physics | Conference |
Volume | ISSN | Citations |
9036 | 0277-786X | 1 |
PageRank | References | Authors |
0.43 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| kent m ogden | 1 | 1 | 1.11 |
| nathaniel ordway | 2 | 1 | 0.43 |
| dalanda diallo | 3 | 1 | 0.43 |
| Gwen Tillapaugh-Fay | 4 | 2 | 1.25 |
| can aslan | 5 | 1 | 0.77 |