Name
Title | ||
|---|---|---|
Automatic Detection Algorithm Based On Lvq Neural Network For Micro-Calcification Clusters |
Abstract | ||
|---|---|---|
Given that the micro-calcification clusters in early breast cancer X-ray pictures are minimal and irregular with differentiated shapes and distributions as well as the unsatisfactorily low contrast ratio, micro-calcification clusters of small sizes and the unsatisfactorily low contrast ratio tend to be easily ignored or misdiagnosed by doctors. This paper applies the LVQ Neural Network to classify micro-calcification clusters as malignant or benign in digitized mammograms based on feature extraction of statistical methods. The result shows the method of LVQ Neural Network is simpler and effective. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-15554-8_47 | HUMAN CENTERED COMPUTING, HCC 2014 |
Keywords | Field | DocType |
Micro-calcification clusters classification, LVQ Neural Network, Tumor pattern | Cluster (physics),Lvq neural network,Pattern recognition,Computer science,Feature extraction,Artificial intelligence,Contrast ratio | Conference |
Volume | ISSN | Citations |
8944 | 0302-9743 | 1 |
PageRank | References | Authors |
0.37 | 8 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ying Kong | 1 | 18 | 6.81 |
| Huijuan Lu | 2 | 112 | 15.51 |