Name
Abstract | ||
|---|---|---|
We present a novel approach to the problem of neuron segmentation in image volumes acquired by an electron microscopy. Existing methods, such as agglomerative or correlation clustering, rely solely on boundary evidence and have problems where such an evidence is lacking (e.g., incomplete staining) or ambiguous (e.g., co-located cell and mitochondria membranes). We investigate if these difficulties... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TMI.2017.2712360 | IEEE Transactions on Medical Imaging |
Keywords | Field | DocType |
Semantics,Image segmentation,Neurons,Labeling,Image edge detection,Biomembranes | Hierarchical clustering,Computer vision,Cutting-plane method,Scale-space segmentation,Pattern recognition,Correlation clustering,Segmentation,Computer science,Image segmentation,Artificial intelligence,Prior probability,Connected-component labeling | Journal |
Volume | Issue | ISSN |
37 | 4 | 0278-0062 |
Citations | PageRank | References |
1 | 0.36 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nikola Krasowski | 1 | 1 | 0.36 |
| Thorsten Beier | 2 | 69 | 5.79 |
| Graham Knott | 3 | 120 | 8.66 |
| Ullrich Koethe | 4 | 249 | 22.37 |
| Fred A. Hamprecht | 5 | 962 | 76.24 |
| Anna Kreshuk | 6 | 8 | 5.02 |