Name
Abstract | ||
|---|---|---|
With the advancement of high throughput and high resolution volumetric brain imaging, there is an unmet need to trace dense neuron fibers and study long-range neuron connectivity. An initial pipeline is described for processing cellular-level neuronal fiber data acquired by a new super resolution imaging method called Magnified Analysis of the Proteome (MAP). First, a multiscale vessel enhancement filter is applied to segment fibers of different diameters. Morphological operations are then employed to extract the fiber centerlines, from which a 3D connectivity map is computed. Applying this approach to an initial data set yielded 2% equal error rate for segmentation and 92% accuracy for end-to-end fiber tracing (22 out of 24 hand-traced fibers). Future work calls for scaling up the algorithm to process much larger brain datasets (terabytes and above) and performing graph-based long-range connectivity analysis. This work has the potential to extend our knowledge on brain networks at the cellular level. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ISBI.2017.7950531 | 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) |
Keywords | Field | DocType |
Brain connectivity,Graph analysis,Image segmentation,Neuron tracing,Target tracking | Computer vision,Fiber,Pattern recognition,Computer science,Segmentation,Word error rate,Image segmentation,Artificial intelligence,Throughput,Neuroimaging,Image resolution,Tracing | Conference |
ISBN | Citations | PageRank |
978-1-5090-1173-5 | 0 | 0.34 |
References | Authors | |
12 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laura J. Brattain | 1 | 27 | 6.64 |
| Brian Telfer | 2 | 0 | 3.72 |
| Siddharth Samsi | 3 | 201 | 24.09 |
| Taeyun Ku | 4 | 0 | 1.01 |
| Heejin Choi | 5 | 4 | 2.89 |
| Kwanghun Chung | 6 | 26 | 4.53 |