Name
Abstract | ||
|---|---|---|
In this paper, we give a new definition of fuzzy contours in mammographic images and we propose an approach to get them. This approach starts from region of interest images with initial contours delimiting masses provided by an expert radiologist, and then it involves three major stages: mass segmentation using geometric deformable models, contour representation and finally definition of fuzzy contours. For the first phase, the initial zero level set is performed by using the initial contour guided by the radiologist. After that, we propose a new representation of contours. Since the segmentation of masses in mammograms is a difficult problem due to the characteristics of mammographic image, and even mass edges can be identified differently by different radiologists and also by the same radiologist at a different time, we define an entire region that may contain the accurate edges, in which we assign to each pixel a membership value to the class "Contour". We call that fuzzy contours. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/IPTA.2015.7367120 | 2015 International Conference on Image Processing Theory, Tools and Applications (IPTA) |
Keywords | Field | DocType |
Mammography,Mass,Fuzyy contours,Geometric deformable models,Segmentation,Contour representation | Computer vision,Scale-space segmentation,Pattern recognition,Segmentation,Computer science,Fuzzy logic,Level set,Image segmentation,Pixel,Artificial intelligence,Region of interest | Conference |
ISSN | ISBN | Citations |
2154-512X | 978-1-4799-8636-1 | 1 |
PageRank | References | Authors |
0.35 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marwa Hmida | 1 | 1 | 0.35 |
| Kamel Hamrouni | 2 | 41 | 21.73 |
| Basel Solaiman | 3 | 127 | 35.05 |