Name
Title | ||
|---|---|---|
Pixel-to-pixel Learning with Weak Supervision for Single-stage Nucleus Recognition in Ki67 Images. |
Abstract | ||
|---|---|---|
Objective: Nucleus recognition is a critical yet challenging step in histopathology image analysis, for example, in Ki67 immunohistochemistry stained images. Although many automated methods have been proposed, most use a multi-stage processing pipeline to categorize nuclei, leading to cumbersome, low-throughput, and error-prone assessments. To address this issue, we propose a novel deep fully conv... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TBME.2019.2900378 | IEEE Transactions on Biomedical Engineering |
Keywords | Field | DocType |
Tumors,Task analysis,Image recognition,Immune system,Feature extraction,Microscopy,Image analysis | Nucleus localization,Computer vision,Nucleus,Task analysis,Computer science,Feature extraction,Image Quantification,Pixel,Artificial intelligence,Region of interest,Artificial neural network | Journal |
Volume | Issue | ISSN |
66 | 11 | 0018-9294 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fuyong Xing | 1 | 378 | 29.02 |
| Toby C Cornish | 2 | 0 | 0.68 |
| Tell Bennett | 3 | 0 | 0.34 |
| Debashis Ghosh | 4 | 496 | 49.16 |
| Lin Yang | 5 | 1291 | 116.88 |