Automatic reconstruction of neural morphologies with multi-scale tracking

Frontiers in Neural Circuits

Volumn , Issue JUNE 2012, 2012, Pages

  Choromanska, Anna ^a   Chang, Shih Fu ^a   Yuste, Rafael ^b  

^a Columbia University ^*  (United States)

^b Och Spine at New York Presbyterian Hospitals   (United States)

Author keywords

Confocal; Dijkstra; Multi scaling; Tracking

Indexed keywords

ACCURACY; ALGORITHM; ARTICLE; CALCULATION; CELL STRUCTURE; CELL TYPE; CEREBELLAR CLIMBING FINGER; DENDRITE; HIPPOCAMPAL CA3 REGION; IMAGE RECONSTRUCTION; NEOCORTICAL LAYER 6 AXON; NERVE CELL; NERVE FIBER; OLFACTORY PROJECTION FIBER; STRUCTURE ANALYSIS;

EID: 84865110867     PISSN: 16625110     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (26)

1. Al-Kofahi, K. A., Lasek, S., Szarowski, D. H., Pace, C. J., Nagy, G., Turner, J. N., and Roysam, B. (2002). Rapid automated three-dimensional tracing of neurons from confocal image stacks. IEEE Trans. Inf. Technol. Biomed. 6, 171-187.
2. Al-Kofahi, Y., Dowell-Mesfin, N., Pace, C., Shain, W., Turner, J. N., and Roysam, B. (2008). Improved detection of branching points in algorithms for automated neuron tracing from 3D confocal images. Cytometry A 73A, 36-43.
3. Brown, K. M., Barrionuevo, G., Canty, A. J., De Paola, V., Hirsch, J. A., Jefferis, G. S. X. E., Lu, J., Snippe, M., Sugihara, I., and Ascoli, G. A. (2011). The DIADEM data sets: representative light microscopy images of neuronal morphology to advance automation of digital reconstructions. Neuroinformatics 9, 143-157.
4. Can, A., Shen, H., Turner, J. N., Tanenbaum, H. L., and Roysam, B. (1999). Rapid automated tracing and feature extraction from retinal fundus images using direct exploratory algorithms. IEEE Trans. Inf. Technol. Biomed. 3, 125-138.
5. Cesar, R. M., Da, L., and Costa, F. (1997). "Semi-automated dendrogram generation for neural shape analysis," in Proceedings of the 10th Brazilian Symposium on Computer Graphics and Image Processing, Campos do Jordão, 147-154.
6. Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik 1, 269-271.
7. Donohue, D. E., and Ascoli, G. A. (2011). Automated reconstruction of neuronal morphology: an overview. Brain Res. Rev. 67, 94-102.
8. Falco, A. X., da Fontoura Costa, L., and da Cunha, B. S. (2002). Multiscale skeletons by image foresting transform and its application to neuromorphometry. Pattern Recognit. 35, 1571-1582.
9. Gillette, T. A., Brown, K. M., Svoboda, K., Liu, Y., and Ascoli, G. A. (2011). DIADEMchallenge.Org: a compendium of resources fostering the continuous development of automated neuronal reconstruction. Neuroinformatics 9, 303-304.
10. Gonzalez, G., Turetken, E., Fleuret, F., and Fua, P. (2010)."Delineating trees in noisy 2D images and 3D image stacks," in Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition, 2010, San Francisco.
11. Janoos, F., Nouansengsy, B., Xu, X., Machiraju, R., and Wong, S. T. C. (2008). Classification and uncertainty visualization of dendritic spines from optical microscopy imaging. Comput. Grap. Forum 27, 879-886.
12. Lichtman, J. W., and Denk, W. (2011). The big and the small: challenges of imaging the brain's circuits. Science 334, 618-623.
13. Lu, J. (2011). Neuronal tracing for connectomic studies. Neuroinformatics 9, 159-166.
14. Lu, J., Fiala, J. C., and Lichtman, J. W. (2009). Semi-automated reconstruction of neural processes from large number of fluorescence images. PLoS ONE 4, e5655. doi:10.1371/journal.pone.0005655
15. Luisi, J., Narayanaswamy, A., Gal-breath, Z., and Roysam, B. (2011). The FARSIGHT trace editor: an open source tool for 3-D inspection and efficient pattern analysis aided editing of automated neuronal reconstructions. Neuroinformatics 9, 305-315.
16. Narayanaswamy, A., Wang, Y., and Roysam, B. (2011). 3-D image pre-processingalgorithmsfor improved automated tracing of neuronal arbors. Neuroinformatics 9, 247-261.
17. Peng, H., Ruan, Z., Long, F., Simpson, J. H., and Myers, E. W. (2010). V3D enables real-time 3D visualization and quantitative analysis of large-scale biological image data sets. Nat. Biotechnol. 28, 348-353.
18. Ropireddy, D., Scorcioni, R., Lasher, B., Buzsaki, G., and Ascoli, G. A.(2011). Axonal morphometry of hippocampal pyramidal neurons semi-automatically reconstructed after in vivo labeling in different CA2 locations. Brain Struct. Funct. 216, 1-15.
19. Schmitt, S., Evers, J. F., Duch, C., Scholz, M., and Obermayer, K. (2004). New methods for the computer-assisted 3-d reconstruction of neurons from confocal image stacks. Neuroimage 23, 1283-1298.
20. Senft, S. L. (2011). A brief history of neuronal reconstruction. Neuroin-formatics 9, 119-128.
21. Srinivasan, R., Li, Q., Zhou, X., Lu, J., Lichtman, J., and Wong, S. T. C. (2010). Reconstruction of the neuromuscular junction connectome. Bioinformatics 26, 64-70.
22. Svoboda, K. (2011). The past, present, and future of single neuron reconstruction. Neuroinformatics 9, 97-98.
23. Vasilkoski, Z., and Stepanyants, A. (2009). Detection of the optimal neuron traces in confocal microscopy images. J. Neurosci. Methods 178, 197-204.
24. Wang, J., Zhou, X., Lu, J., Lichtman, J., Chang, S. F., and Wong, S. T. C. (2007). "Dynamic local tracing for 3d axon curvilinear structure detection from microscopic image stack," in ISBI'07, Washington, 81-84.
25. Wang, Y., Narayanaswamy, A., Tsai, C.L., and Roysam, B. (2011). A broadly applicable3-D neuron tracing method based on open-curve snake. Neuroinformatics 9, 193-217.
26. Yuan, X., Trachtenberg, J., Potter, S., and Roysam, B. (2009). MDL constrained 3-D grayscale skeletonization algorithm for automated extraction of dendrites and spines from fluorescence confocal images. Neuroinformatics 7, 213-232.