Name
Title | ||
|---|---|---|
Recognizing Focal Liver Lesions in CEUS With Dynamically Trained Latent Structured Models. |
Abstract | ||
|---|---|---|
This work investigates how to automatically classify Focal Liver Lesions (FLLs) into three specific benign or malignant types in Contrast-Enhanced Ultrasound (CEUS) videos, and aims at providing a computational framework to assist clinicians in FLL diagnosis. The main challenge for this task is that FLLs in CEUS videos often show diverse enhancement patterns at different temporal phases. To handle... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TMI.2015.2492618 | IEEE Transactions on Medical Imaging |
Keywords | Field | DocType |
Frequency locked loops,Videos,Lesions,Cancer,Liver,Computational modeling,Ultrasonic imaging | Computer vision,Dynamic programming,Inference,Computer science,Parameter learning,Artificial intelligence,Discriminative model,Optimization problem,Machine learning,Ultrasonic imaging,Model learning | Journal |
Volume | Issue | ISSN |
35 | 3 | 0278-0062 |
Citations | PageRank | References |
4 | 0.69 | 27 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaodan Liang | 1 | 1096 | 77.53 |
| Liang Lin | 2 | 3007 | 151.07 |
| Qingxing Cao | 3 | 13 | 2.61 |
| Rui Huang | 4 | 118 | 4.33 |
| Yongtian Wang | 5 | 456 | 73.00 |