Name
Title | ||
|---|---|---|
Accurate Segmentation of CT Male Pelvic Organs via Regression-based Deformable Models and Multi-task Random Forests. |
Abstract | ||
|---|---|---|
Segmenting male pelvic organs from CT images is a prerequisite for prostate cancer radiotherapy. The efficacy of radiation treatment highly depends on segmentation accuracy. However, accurate segmentation of male pelvic organs is challenging due to low tissue contrast of CT images, as well as large variations of shape and appearance of the pelvic organs. Among existing segmentation methods, deform... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TMI.2016.2519264 | IEEE Transactions on Medical Imaging |
Keywords | Field | DocType |
Image segmentation,Computed tomography,Deformable models,Shape,Bladder,Planning | Voxel,Computer vision,Decision tree,Regression,Segmentation,Image segmentation,Artificial intelligence,Initialization,Classifier (linguistics),Random forest,Mathematics | Journal |
Volume | Issue | ISSN |
35 | 6 | 0278-0062 |
Citations | PageRank | References |
15 | 0.68 | 21 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yaozong Gao | 1 | 626 | 47.13 |
| Yeqin Shao | 2 | 39 | 4.73 |
| Jun Lian | 3 | 15 | 0.68 |
| Andrew Wang | 4 | 19 | 1.52 |
| Ronald Chen | 5 | 16 | 2.04 |
| Dinggang Shen | 6 | 7837 | 611.27 |