Name
Title | ||
|---|---|---|
Analysis Of Supervised And Semi-Supervised Growcut Applied To Segmentation Of Masses Inmammography Images |
Abstract | ||
|---|---|---|
Breast cancer is already one of the most common form of cancer worldwide. Mammography image analysis is still the most effective diagnostic method to promote the early detection of breast cancer. Accurately segmenting tumours in digital mammography images is important to improve diagnosis capabilities of health specialists and avoid misdiagnosis. In this work, we evaluate the feasibility of applying GrowCut to segment regions of tumour and we propose two GrowCut semi-supervised versions. All the analyses were performed by evaluating the application of segmentation techniques to a set of images obtained from the Mini-MIAS mammography image database. GrowCut segmentation was compared to Region Growing, Active Contours, Random Walks and Graph Cut techniques. Experiments showed that GrowCut, when compared to the other techniques, was able to acquire better results for the metrics analysed. Moreover, the proposed semi-supervised versions of GrowCut were proved to have a clinically satisfactory quality of segmentation. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1080/21681163.2015.1127775 | COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION |
Keywords | DocType | Volume |
Mammography, mass segmentation, GrowCut, breast cancer, mass detection, mass classification | Journal | 5 |
Issue | ISSN | Citations |
4 | 2168-1163 | 1 |
PageRank | References | Authors |
0.35 | 15 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| F. R. Cordeiro | 1 | 46 | 7.14 |
| Wellington P. dos Santos | 2 | 36 | 11.00 |
| Abel Guilhermino Silva-Filho | 3 | 62 | 12.94 |