• Journal of Innovative Optical Health Sciences
  • Vol. 16, Issue 6, 2340006 (2023)
Lanlan Li1, Jing Qi1, Yi Geng1, and Jingpeng Wu2,*
Author Affiliations
  • 1Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou, Fujian 350116, P. R. China
  • 2Center for Computational Neuroscience, Flatiron Institute, New York 10010, USA
  • show less
    DOI: 10.1142/S1793545823400060 Cite this Article
    Lanlan Li, Jing Qi, Yi Geng, Jingpeng Wu. Semantic segmentation of pyramidal neuron skeletons using geometric deep learning[J]. Journal of Innovative Optical Health Sciences, 2023, 16(6): 2340006 Copy Citation Text show less
    References

    [1] B. Ljungquist, M. A. Akram, G. A. Ascoli. Large scale similarity search across digital reconstructions of neural morphology. Neurosci. Res., 181, 39-45(2022).

    [2] S. Ramón y Cajal. 1909–1911 Histologie du système nerveux de l’homme et des vertébrés, 2(1952).

    [3] L. W. Swanson, J. W. Lichtman. From Cajal to connectome and beyond. Annu. Rev. Neurosci., 39, 197-216(2016).

    [4] E. D. De Robertis, H. S. Bennett. Some features of the submicroscopic morphology of synapses in frog and earthworm. J. Cell Biol., 1, 47-58(1955).

    [5] Y. LeCun, Y. Bengio, G. Hinton. Deep learning. Nature, 521, 436-444(2015).

    [6] T. Macrina et al. Petascale neural circuit reconstruction: Automated methods(2021).

    [7] K. Shaga Devan, H. A. Kestler, C. Read, P. Walther. Weighted average ensemble-based semantic segmentation in biological electron microscopy images. Histochem. Cell Biol., 158, 447-462(2022).

    [8] Y. Jiang, W. Chen, M. Liu, Y. Wang, E. Meijering. 3D neuron microscopy image segmentation via the ray-shooting model and a DC-BLSTM network. IEEE Trans. Med. Imag., 40, 26-37(2020).

    [9] M. Koziński, A. Mosinska, M. Salzmann, P. Fua. Tracing in 2D to reduce the annotation effort for 3D deep delineation of linear structures. Med. Image Anal., 60, 101590(2020).

    [10] W. Chen, M. Liu, H. Du, M. Radojević, Y. Wang, E. Meijering. Deep-learning-based automated neuron reconstruction from 3D microscopy images using synthetic training images. IEEE Trans. Med. Imag., 41, 1031-1042(2021).

    [11] A. Mosinska, M. Koziński, P. Fua. Joint segmentation and path classification of curvilinear structures. IEEE Trans. Pattern Anal. Mach. Intell., 42, 1515-1521(2019).

    [12] B. Yang, M. Liu, Y. Wang, K. Zhang, E. Meijering. Structure-guided segmentation for 3D neuron reconstruction. IEEE Trans. Med. Imag., 41, 903-914(2021).

    [13] L. Luo. Fly MARCM and mouse MADM: Genetic methods of labeling and manipulating single neurons. Brain Res. Rev., 55, 220-227(2007).

    [14] L. Luo, E. M. Callaway, K. Svoboda. Genetic dissection of neural circuits. Neuron, 57, 634-660(2008).

    [15] H. Cuntz, F. Forstner, A. Borst, M. Häusser. The TREES toolbox—probing the basis of axonal and dendritic branching. Neuroinformatics, 9, 91-96(2011).

    [16] R. Scorcioni, S. Polavaram, G. A. Ascoli. L-Measure: A web-accessible tool for the analysis, comparison and search of digital reconstructions of neuronal morphologies. Nat. Protocols, 3, 866-876(2008).

    [17] J. Wu, N. Turner, J. A. Bae, A. Vishwanathan, H. S. Seung. RealNeuralNetworks. jl: An integrated julia package for skeletonization, morphological analysis, and synaptic connectivity analysis of terabyte-scale 3D neural segmentations. Front. Neuroinf., 16, 828169(2022).

    [18] B. Celii et al. NEURD: A mesh decomposition framework for automated proofreading and morphological analysis of neuronal EM reconstructions(2023).

    [19] M. M. Bronstein, J. Bruna, Y. LeCun, A. Szlam, P. VandergheynstIEEE Signal Process. Mag. Geometric deep learning: Going beyond euclidean data, 34, 18-42(2017).

    [20] W. Cao, Z. Yan, Z. He, Z. He. A comprehensive survey on geometric deep learning. IEEE Access, 8, 35929-35949(2020).

    [21] S. Dorkenwald et al. Binary and analog variation of synapses between cortical pyramidal neurons. Elife, 11, e76120(2022).

    [22] P. J. Schubert, S. Dorkenwald, M. Januszewski, V. Jain, J. Kornfeld. Learning cellular morphology with neural networks. Nat. Commun., 10, 2736(2019).

    [23] P. J. Schubert et al. SyConn2: Dense synaptic connectivity inference for volume electron microscopy. Nat. Meth., 19, 1-4(2022).

    [24] S. Seshamani et al. Automated neuron shape analysis from electron microscopy(2020).

    [25] M. A. Weis et al. Large-scale unsupervised discovery of excitatory morphological cell types in mouse visual cortex, 521541(2022).

    [26] G. A. Ascoli, D. E. Donohue, M. Halavi. NeuroMorpho. Org: A central resource for neuronal morphologies. J. Neurosci., 27, 9247-9251(2007).

    [27] G. N. Elston. Cortex, cognition and the cell: New insights into the pyramidal neuron and prefrontal function. Cereb. Cortex, 13, 1124-1138(2003).

    [28] J. M. Bekkers. Pyramidal neurons. Curr. Biol., 21, R975(2011).

    [29] Q.-Y. Zhou, J. Park, V. Koltun. Open3D: A modern library for 3D data processing(2018).

    [30] W. He, Z. Jiang, C. Zhang, A. M. Sainju. CurvaNet: Geometric deep learning based on directional curvature for 3D shape analysis. Proc. 26th ACM SIGKDD Int. Conf. Knowledge Discovery & Data Mining, 2214-2224(2020).

    [31] A. Sinha, J. Bai, K. Ramani. Deep learning 3D shape surfaces using geometry images. Computer Vision–ECCV 2016, 9910, 223-240(2016).

    [32] C. R. Qi, H. Su, K. Mo, L. J. Guibas. Pointnet: Deep learning on point sets for 3d classification and segmentation. Proc. IEEE Conf. Computer Vision and Pattern Recognition, 652-660(2017).

    Lanlan Li, Jing Qi, Yi Geng, Jingpeng Wu. Semantic segmentation of pyramidal neuron skeletons using geometric deep learning[J]. Journal of Innovative Optical Health Sciences, 2023, 16(6): 2340006
    Download Citation