Name
Abstract | ||
|---|---|---|
Our purpose in this study is to develop a scheme to segment the rectus abdominis muscle region in X-ray CT images. We propose a new muscle recognition method based on the shape model. In this method, three steps are included in the segmentation process. The first is to generate a shape model for representing the rectus abdominis muscle. The second is to recognize anatomical feature points corresponding to the origin and insertion of the muscle, and the third is to segment the rectus abdominis muscles using the shape model. We generated the shape model from 20 CT cases and tested the model to recognize the muscle in 10 other CT cases. The average value of the Jaccard similarity coefficient (JSC) between the manually and automatically segmented regions was 0.843. The results suggest the validity of the model-based segmentation for the rectus abdominis muscle. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1587/transinf.E96.D.869 | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS |
Keywords | Field | DocType |
abdominal muscles, X-ray CT images, shape model, segmentation | Computer vision,Rectus abdominis muscle,Anatomical feature,Pattern recognition,Computer science,Segmentation,Artificial intelligence,Jaccard index | Journal |
Volume | Issue | ISSN |
E96D | 4 | 0916-8532 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Naoki Kamiya | 1 | 1 | 0.70 |
| Xiangrong Zhou | 2 | 325 | 45.53 |
| Huayue Chen | 3 | 41 | 8.90 |
| Chisako Muramatsu | 4 | 317 | 35.56 |
| Takeshi Hara | 5 | 639 | 79.10 |
| Hiroshi Fujita | 6 | 0 | 0.34 |