Name
Title | ||
|---|---|---|
Integrated local binary pattern texture features for classification of breast tissue imaged by optical coherence microscopy. |
Abstract | ||
|---|---|---|
•Texture analysis is applied on OCM images for human breast tissue classification.•New variants of local binary pattern (LBP) are proposed to extract texture features.•Using multi-scale and integrated image features improves classification accuracy.•Achieved high sensitivity (100%) and specificity (85.2%) for cancer detection. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.media.2017.03.002 | Medical Image Analysis |
Keywords | Field | DocType |
Optical coherence microscopy,Tissue classification,Texture features,Local binary patterns | Lobular carcinoma,Ductal carcinoma,Computer vision,Receiver operating characteristic,Feature selection,Pattern recognition,Fibroadenoma,Local binary patterns,Ground truth,Artificial intelligence,Pixel,Mathematics | Journal |
Volume | ISSN | Citations |
38 | 1361-8415 | 5 |
PageRank | References | Authors |
0.42 | 33 | 11 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sunhua Wan | 1 | 7 | 1.15 |
| Hsiang-Chieh Lee | 2 | 7 | 1.48 |
| Xiaolei Huang | 3 | 1084 | 63.94 |
| Ting Xu | 4 | 23 | 2.21 |
| Tao Xu | 5 | 8 | 1.47 |
| Xianxu Zeng | 6 | 8 | 1.13 |
| Zhan Zhang | 7 | 19 | 10.81 |
| Yuri Sheikine | 8 | 5 | 0.42 |
| James L. Connolly | 9 | 5 | 0.42 |
| James G. Fujimoto | 10 | 12 | 6.61 |
| Chao Zhou | 11 | 7 | 1.82 |