Automated algorithms for multiscale morphometry of neuronal dendrites
Neural Computation
Filament tracking and encoding for complex biological networks
Proceedings of the 2008 ACM symposium on Solid and physical modeling
Identifying, tabulating, and analyzing contacts between branched neuron morphologies
IBM Journal of Research and Development
3D Dendrite Reconstruction and Spine Identification
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
A statistical assembled deformable model (SAMTUS) for vasculature reconstruction
Computers in Biology and Medicine
Steerable Features for Statistical 3D Dendrite Detection
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Fast and accurate retinal vasculature tracing and kernel-Isomap-based feature selection
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Equilibrium modeling for 3D curvilinear structure tracking of confocal microscopy images
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Automatic and reliable extraction of dendrite backbone from optical microscopy images
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part III
Automatic neuron tracing in volumetric microscopy images with anisotropic path searching
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
Fast extraction of neuron morphologies from large-scale SBFSEM image stacks
Journal of Computational Neuroscience
Automatic reconstruction of dendrite morphology from optical section stacks
CVAMIA'06 Proceedings of the Second ECCV international conference on Computer Vision Approaches to Medical Image Analysis
Multilayer neural networks with receptive fields as a model for the neuron reconstruction problem
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part II
Journal of Visual Communication and Image Representation
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Classification and uncertainty visualization of dendritic spines from optical microscopy imaging
EuroVis'08 Proceedings of the 10th Joint Eurographics / IEEE - VGTC conference on Visualization
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Algorithms are presented for fully automatic three-dimensional (3D) tracing of neurons that are imaged by fluorescence confocal microscopy. Unlike previous voxel-based skeletonization methods, the present approach works by recursively following the neuronal topology, using a set of 4 \× N 2 directional kernels (e.g., N = 32), guided by a generalized 3D cylinder model. This method extends our prior work on exploratory tracing of retinal vasculature to 3D space. Since the centerlines are of primary interest, the 3D extension can be accomplished by four rather than six sets of kernels. Additional modifications, such as dynamic adaptation of the correlation kernels, and adaptive step size estimation, were introduced for achieving robustness to photon noise, varying contrast, and apparent discontinuity and/or hollowness of structures. The end product is a labeling of all somas present, graph-theoretic representations of all dendritic/axonal structures, and image statistics such as soma volume and centroid, soma interconnectivity, the longest branch, and lengths of all graph branches originating from a soma. This method is able to work directly with unprocessed confocal images, without expensive deconvolution or other preprocessing. It is much faster that skeletonization, typically consuming less than a minute to trace a 70 MB image on a 500 MHz computer. These properties make it attractive for large-scale automated tissue studies that require rapid on-line image analysis, such as high-throughput neurobiology/angiogenesis assays, and initiatives such as the Human Brain Project.