Name
Abstract | ||
|---|---|---|
Considering the importance of early diagnosis of breast cancer, a supervised patch-wise texton-based approach has been developed for the classification of mass abnormalities in mammograms. The proposed method is based on texture-based classification of masses in mammograms and does not require segmentation of the mass region. In this approach, patches from filter bank responses are utilised for ge... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1049/iet-cvi.2018.5244 | IET Computer Vision |
Keywords | Field | DocType |
Bayes methods,cancer,channel bank filters,image classification,image texture,mammography,medical image processing,object detection | Receiver operating characteristic,Naive Bayes classifier,Mass classification,Pattern recognition,Texton,Segmentation,Filter bank,Artificial intelligence,Mathematics,Screening mammography | Journal |
Volume | Issue | ISSN |
12 | 8 | 1751-9632 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zobia Suhail | 1 | 9 | 3.32 |
| Azam Hamidinekoo | 2 | 19 | 3.48 |
| R Zwiggelaar | 3 | 91 | 7.18 |