Name
Abstract | ||
|---|---|---|
In this paper we study the identification of masses in digital mammograms using texture analysis. A number of texture measures are calculated for bilateral difference images showing regions of interest. The measurements are made on co- occurrence matrices in four different direction giving a total of seventy features. These features include the ones proposed by Haralick et. al., (1973) and (Chan et al., 1997). We study a total of 144 breast images from the MIAS database. The dimensionality of the dataset is reduced using principal components analysis (PCA). PCA components are classified using both multilayer perceptron networks using backpropagation (MLP) and radial basis functions based on Gaussian kernels (RBF). The two methods are compared on the same data across a ten fold cross-validation. The results are generated on the average recognition rate over these folds on correctly recognising masses and normal regions. Further analysis is based on the Receiver Operating Characteristic (ROC) plots. The best results show recognition rates of 77% correct recognition and an area under the ROC curve value Az of 0.74. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1109/IJCNN.2000.857859 | Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference |
Keywords | Field | DocType |
feature extraction,image texture,mammography,medical image processing,multilayer perceptrons,principal component analysis,radial basis function networks,Gaussian kernels,MIAS database,MLP,PCA,RBF nets,ROC plots,backpropagation,bilateral difference images,breast images,breast scanning,co-occurrence matrices,digital mammograms,mass identification,multilayer perceptron,principal components analysis,receiver operating characteristic plots,texture analysis | Receiver operating characteristic,Radial basis function,Pattern recognition,Computer science,Image texture,Feature extraction,Gaussian,Multilayer perceptron,Artificial intelligence,Backpropagation,Machine learning,Principal component analysis | Conference |
Volume | ISSN | ISBN |
1 | 1098-7576 | 0-7695-0619-4 |
Citations | PageRank | References |
21 | 1.44 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Keir Bovis | 1 | 72 | 4.82 |
| Sameer Singh | 2 | 1657 | 108.24 |
| Jonathan E. Fieldsend | 3 | 21 | 1.44 |
| Chris Pinder | 4 | 21 | 1.44 |