Name
Abstract | ||
|---|---|---|
•An automatic system for mass segmentation in regions of interest extracted from mammograms.•Fuzzy contours formalism allow dealing with imprecision inherent to contour localization.•Introducing fuzzy contours as a constraint which restrains the evolution of the Chan–Vese model in order to properly extract the accurate mass contour.•Reducing false positives caused by inhomogeneity in region of interest tissue.•The proposed method provides an accurate and reliable results compared to ground truth images and previous work. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.cmpb.2018.07.005 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
Mass segmentation,Mammography,Active contours,Fuzzy contours | Computer vision,Segmentation,Computer science,Fuzzy logic,Feature extraction,Ground truth,Artificial intelligence,Region of interest,Initialization,True positive rate | Journal |
Volume | ISSN | Citations |
164 | 0169-2607 | 0 |
PageRank | References | Authors |
0.34 | 27 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marwa Hmida | 1 | 0 | 0.34 |
| Kamel Hamrouni | 2 | 41 | 21.73 |
| Basel Solaiman | 3 | 127 | 35.05 |
| Sana Boussetta | 4 | 0 | 0.34 |