Name
Abstract | ||
|---|---|---|
•It points out detailed quantitative anatomic (QA) information currently not existing.•We demonstrate the non-linear geometric and geographic relationships among objects.•We show the highly non-linear variations of object-specific properties of 11 objects.•QA information is useful in creating effective models for the object segmentation. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.compmedimag.2016.03.005 | Computerized Medical Imaging and Graphics |
Keywords | Field | DocType |
Thorax,CT,Quantification,Quantitative radiology,Automatic anatomy recognition,Segmentation | Computer vision,Anatomy,Visualization,Segmentation,Thorax,Correlation,Artificial intelligence,Geography,Thoracic region,Left lungs | Journal |
Volume | ISSN | Citations |
51 | 0895-6111 | 1 |
PageRank | References | Authors |
0.36 | 16 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Monica M. S. Matsumoto | 1 | 39 | 5.57 |
| Jayaram K. Udupa | 2 | 2481 | 322.29 |
| Yubing Tong | 3 | 93 | 22.73 |
| Babak Saboury | 4 | 48 | 5.96 |
| D. A. Torigian | 5 | 81 | 21.68 |