Name
Abstract | ||
|---|---|---|
We propose a technique for automatic spinal deformity detection method from moire topographic images. Normally the moire stripes show a symmetric pattern, as a human body is almost symmetric. According to the progress of the deformity of a spine, asymmetry becomes larger. Numerical representation of the degree of asymmetry is therefore useful in evaluating the deformity. Displacement of local centroids is evaluated statistically between the left-hand side and the right-hand side regions of the moire images with respect to the extracted middle line. The degree of the displacement learned by a neural network employing the back propagation algorithm. An experiment was performed employing 1,200 real moire images (600 normal and 600 abnormal) and 89% of the images were classified correctly by the NN. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/978-3-540-39899-8_98 | LECTURE NOTES IN COMPUTER SCIENCE |
Keywords | Field | DocType |
neural network,human body | Moiré pattern,Back propagation algorithm,Computer vision,Pattern recognition,Topographic map,Computer science,Artificial intelligence,Artificial neural network,Asymmetry,Centroid,Deformity | Conference |
Volume | ISSN | Citations |
2878 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 4 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hyoungseop Kim | 1 | 293 | 36.05 |
| Seiji Ishikawa | 2 | 342 | 49.06 |
| Marzuki Khalid | 3 | 3 | 1.81 |
| Yoshinori Otsuka | 4 | 12 | 3.75 |
| Hisashi Shimizu | 5 | 5 | 1.67 |
| Yasuhiro Nakada | 6 | 0 | 0.34 |
| Takashi Shinomiya | 7 | 6 | 3.38 |
| Max A Viergever | 8 | 7946 | 833.77 |