Name
Title | ||
|---|---|---|
Deep Learning Segmentation of Optical Microscopy Images Improves 3-D Neuron Reconstruction. |
Abstract | ||
|---|---|---|
Digital reconstruction, or tracing, of 3-D neuron structure from microscopy images is a critical step toward reversing engineering the wiring and anatomy of a brain. Despite a number of prior attempts, this task remains very challenging, especially when images are contaminated by noises or have discontinued segments of neurite patterns. An approach for addressing such problems is to identify the l... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TMI.2017.2679713 | IEEE Transactions on Medical Imaging |
Keywords | Field | DocType |
Neurons,Three-dimensional displays,Image reconstruction,Convolution,Image segmentation,Microscopy,Morphology | Iterative reconstruction,Computer vision,Scale-space segmentation,Convolutional neural network,Segmentation,Computer science,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Deep learning,Tracing | Journal |
Volume | Issue | ISSN |
36 | 7 | 0278-0062 |
Citations | PageRank | References |
13 | 0.55 | 23 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rongjian Li | 1 | 13 | 0.55 |
| Tao Zeng | 2 | 71 | 5.21 |
| Hanchuan Peng | 3 | 3930 | 182.27 |
| Shuiwang Ji | 4 | 2579 | 122.25 |