Name
Abstract | ||
|---|---|---|
We developed a novel de-arraying approach for TMA analysis. By combining wavelet-based detection, active contour segmentation, and thin-plate spline interpolation, our approach is able to handle TMA images with high dynamic, poor signal-to-noise ratio, complex background and non-linear deformation of TMA grid. In addition, the deformation estimation produces quantitative information to asset the manufacturing quality of TMAs. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s12859-018-2111-8 | BMC Bioinformatics |
Keywords | Field | DocType |
Active contour,Deformation,Detection,Segmentation,TMA de-arraying,Thin-plate spline,Tissue microarray,Wavelet | Active contour model,Computer vision,Bottleneck,Segmentation,Multiplex,Tissue microarray,Artificial intelligence,Engineering,DNA microarray,Manufacturing process,Grid | Journal |
Volume | Issue | ISSN |
19 | 1 | 1471-2105 |
Citations | PageRank | References |
0 | 0.34 | 17 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hoai-Nam Nguyen | 1 | 0 | 1.01 |
| Vincent Paveau | 2 | 1 | 1.03 |
| Cyril Cauchois | 3 | 1 | 1.03 |
| Charles Kervrann | 4 | 934 | 67.36 |