Name
Abstract | ||
|---|---|---|
Volumetric ultrasound is rapidly emerging as a viable imaging modality for routine prenatal examinations. Biometrics obtained from the volumetric segmentation shed light on the reformation of precise maternal and fetal health monitoring. However, the poor image quality, low contrast, boundary ambiguity, and complex anatomy shapes conspire toward a great lack of efficient tools for the segmentation... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TMI.2018.2858779 | IEEE Transactions on Medical Imaging |
Keywords | Field | DocType |
Ultrasonic imaging,Three-dimensional displays,Fetus,Semantics,Image segmentation,Shape,Labeling | Computer vision,Data set,Segmentation,Recurrent neural network,Image quality,Image segmentation,Artificial intelligence,Biometrics,Ambiguity,Semantics,Mathematics | Journal |
Volume | Issue | ISSN |
38 | 1 | 0278-0062 |
Citations | PageRank | References |
7 | 0.57 | 0 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xin Yang | 1 | 175 | 12.96 |
| Lequan Yu | 2 | 706 | 39.80 |
| Shengli Li | 3 | 184 | 18.06 |
| Huaxuan Wen | 4 | 7 | 0.57 |
| Dandan Luo | 5 | 7 | 0.57 |
| Cheng Bian | 6 | 26 | 4.00 |
| Jing Qin | 7 | 1109 | 95.43 |
| Dong Ni | 8 | 367 | 37.37 |
| Pheng-Ann Heng | 9 | 3565 | 280.98 |