Name
Title | ||
|---|---|---|
A Robust Approach for Mammographic Image Classification Using NSVC Algorithm: Extended Abstract |
Abstract | ||
|---|---|---|
Nowadays, classification is the most efficient method for breast cancer detection using mammography images. During the last two decades, researchers achieved very good results using different kinds of classification methods. In this context, we will focus in this work on the quality of mammography image classification by proposing a new approach that we compares with the state-of-art methods. Our methods consists of two phases; a semi-supervised step based on SKDA and a second step based on SVM. As will be shown in the experiments section, results on Mammography data set show that the proposed algorithm can get very good results. The best precision obtained by NSVC exceeded 99 %. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1145/3038884.3038892 | MedPRAI |
DocType | ISBN | Citations |
Conference | 978-1-4503-4876-8 | 0 |
PageRank | References | Authors |
0.34 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammed Ngadi | 1 | 0 | 0.34 |
| Aouatif Amine | 2 | 85 | 9.29 |
| Bouchra Nassih | 3 | 0 | 0.34 |