Name
Title | ||
|---|---|---|
Choquet Integral based Feature Selection for Early Breast Cancer Diagnosis from MRIs. |
Abstract | ||
|---|---|---|
This paper focuses on breast cancer of the mammary gland. Both basic segmentation steps and usual featuresare recalled. Then textural and morphological information are combined to improve the overall performanceof breast MRI in a computer-aided system. A model of selection based on Choquet integral is provided. Suchmodel is suitable when handling with a weak amount of data even ambiguous in some extent. Achieved resultscompared to well-known classification methods show the interest of our approach. |
Year | Venue | Field |
|---|---|---|
2016 | ICPRAM | Mammography,Feature selection,Breast cancer,Pattern recognition,Segmentation,Computer science,Computer-aided diagnosis,Breast MRI,Mammary gland,Artificial intelligence,Choquet integral,Machine learning |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Soumaya Trabelsi Ben Ameur | 1 | 0 | 0.68 |
| Florence Cloppet | 2 | 42 | 8.16 |
| Dorra Sellami Masmoudi | 3 | 42 | 8.85 |
| Laurent Wendling | 4 | 225 | 28.98 |