Name
Title | ||
|---|---|---|
Computer-Aided Medical Image Annotation: Preliminary Results With Liver Lesions in CT. |
Abstract | ||
|---|---|---|
The increasing volume of medical image data, as well as the need for multicenter data consolidation for big data analytics, require computer-aided medical image annotation (CMIA). Majority of the methods proposed so far do not exploit interdependencies between annotations explicitly. They further limit their annotations at a higher level than diagnostics and/or do not consider a standardized lexic... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/JBHI.2017.2771211 | IEEE Journal of Biomedical and Health Informatics |
Keywords | Field | DocType |
Biomedical imaging,Liver,Lesions,Semantics,Computational modeling,Support vector machines,Computed tomography | Computer vision,Automatic image annotation,Annotation,Medical imaging,Computer science,Computer-aided,Support vector machine,Artificial intelligence,Big data,Network model,Bayesian probability | Journal |
Volume | Issue | ISSN |
22 | 5 | 2168-2194 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Neda Barzegar Marvasti | 1 | 63 | 6.03 |
| Erdem Yörük | 2 | 126 | 8.73 |
| Burak Acar | 3 | 326 | 27.19 |