Name
Title | ||
|---|---|---|
A New Unsupervised Approach for Segmenting and Counting Cells in High-Throughput Microscopy Image Sets. |
Abstract | ||
|---|---|---|
New technological advances in automated microscopy have given rise to large volumes of data, which have made human-based analysis infeasible, heightening the need for automatic systems for high-throughput microscopy applications. In particular, in the field of fluorescence microscopy, automatic tools for image analysis are making an essential contribution in order to increase the statistical power... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/JBHI.2018.2817485 | IEEE Journal of Biomedical and Health Informatics |
Keywords | Field | DocType |
Image segmentation,Microscopy,Transforms,Biology,Pipelines,Morphological operations,Task analysis | Computer vision,Counting process,Pattern recognition,Computer science,Segmentation,Image segmentation,Foreground detection,Distance transform,Artificial intelligence,Region growing,Thresholding,Cluster analysis | Journal |
Volume | Issue | ISSN |
23 | 1 | 2168-2194 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel Riccio | 1 | 170 | 23.60 |
| Nadia Brancati | 2 | 29 | 7.76 |
| Maria Frucci | 3 | 190 | 26.24 |
| Diego Gragnaniello | 4 | 162 | 12.51 |