To search, Click below search items. |
| All Published Papers Search Service |
|
|
|
Title |
Gray Tone Spatial Dependence Matrices based Classification of Breast Mammograms |
|
Author |
M. Arfan Jaffar |
| Citation |
Vol. 17 No. 5 pp. 37-43 |
|
Abstract |
Texture plays an important role for classification of images based upon texture information. Breast mammograms have also texture so for these type of images, texture can be helpful for classification. Breast mammograms can be used to analyze the breast cancer specially for women. In this paper, gray tone spatial dependence matrices have been used for texture analysis and for feature extractions. After that, artificial neural network has been used for classification of breast mammograms by using the texture features. Before features extraction, region of interest has been calculated manually by using the information provided in the dataset. So for features extraction, these ROI images has been used for classification. A well-known standard dataset (DDMS) has been used for verification of proposed method. Different classifiers have been compared to test which classifier is most suitable for this problem. Results shows that proposed method has attained 96.13% accuracy as well as 98.38% sensitivity and 96.23 specificity. |
|
Keywords |
breast mammograms, gray tone, spatial dependence, classification, texture |
|
URL |
