Name
Abstract | ||
|---|---|---|
The quality of ultrasound (US) images for the obstetric examination is crucial for accurate biometric measurement. However, manual quality control is a labor intensive process and often impractical in a clinical setting. To improve the efficiency of examination and alleviate the measurement error caused by improper US scanning operation and slice selection, a computerized fetal US image quality as... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TCYB.2017.2671898 | IEEE Transactions on Cybernetics |
Keywords | Field | DocType |
Biomedical imaging,Standards,Quality control,Ultrasonic imaging,Image quality,Biomedical measurement,Quality assessment | Computer vision,Obstetric examination,Medical imaging,Convolutional neural network,Image quality,Artificial intelligence,Region of interest,Biometrics,Artificial neural network,Ultrasound image,Mathematics | Journal |
Volume | Issue | ISSN |
47 | 5 | 2168-2267 |
Citations | PageRank | References |
10 | 0.50 | 23 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lingyun Wu | 1 | 22 | 1.37 |
| Jie-Zhi Cheng | 2 | 102 | 13.00 |
| Shengli Li | 3 | 184 | 18.06 |
| Bai Ying Lei | 4 | 119 | 24.99 |
| Tianfu Wang | 5 | 382 | 55.46 |
| Dong Ni | 6 | 367 | 37.37 |