Name
Title | ||
|---|---|---|
Differential diagnosis of CT focal liver lesions using texture features, feature selection and ensemble driven classifiers |
Abstract | ||
|---|---|---|
Conclusions The comparative assessment of the various CAD architectures shows that combining three types of classifiers with a voting scheme, fed with identical feature sets obtained after appropriate feature selection and fusion, may result in an accurate system able to assist differential diagnosis of focal liver lesions from non-enhanced CT images. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.artmed.2007.05.002 | Artificial Intelligence in Medicine |
Keywords | Field | DocType |
Liver CT images,Computer-aided diagnosis,Texture features,Ensembles of classifiers,Genetic algorithms,Bootstrap,Feature selection | CAD,Ensembles of classifiers,Pattern recognition,Hepatocellular carcinoma,Feature selection,Computer science,Computer-aided diagnosis,Hemangioma,Artificial intelligence,Hepatic Cyst,Machine learning,Differential diagnosis | Journal |
Volume | Issue | ISSN |
41 | 1 | 0933-3657 |
Citations | PageRank | References |
27 | 1.93 | 21 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stavroula G Mougiakakou | 1 | 342 | 28.61 |
| Ioannis Valavanis | 2 | 94 | 11.72 |
| Alexandra Nikita | 3 | 27 | 2.27 |
| Konstantina S. Nikita | 4 | 448 | 66.23 |