Name
Abstract | ||
|---|---|---|
The unsupervised region proposing method can generate regions as predictions of lesions in histopathological WSI. The region proposals can also serve as the training samples to train machine-learning models for image retrieval. The proposed hashing method can achieve fast and precise image retrieval with small amount of labels. Furthermore, the proposed methods can be potentially applied in online computer-aided-diagnosis systems. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.cmpb.2018.02.020 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
Whole slide image,Region proposal,Selective Search,Content-based image retrieval,Latent Dirichlet allocation,Supervised hashing | Computer vision,Latent Dirichlet allocation,Color space,Computer science,Effective method,Image retrieval,Hash function,Artificial intelligence,Binary number | Journal |
Volume | ISSN | Citations |
159 | 0169-2607 | 2 |
PageRank | References | Authors |
0.38 | 15 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yibing Ma | 1 | 31 | 4.41 |
| Zhiguo Jiang | 2 | 321 | 45.58 |
| Haopeng Zhang | 3 | 47 | 14.75 |
| Fengying Xie | 4 | 182 | 15.33 |
| Yushan Zheng | 5 | 34 | 6.11 |
| Huaqiang Shi | 6 | 17 | 2.30 |
| Yu Zhao | 7 | 20 | 2.74 |
| Jun Shi | 8 | 51 | 5.23 |