DYNAMIC LOCAL TRACING FOR 3D AXON CURVILINEAR STRUCTURE DETECTION FROM MICROSCOPIC IMAGE STACK

To study the morphologic structure of axons can help neuro-scientists understand the neuronal function and development. The modern microscopes provide the fundamental tool for visual inspection of axonal structure. Due to the high volume of generated microscopic axon image data, it is critical to develop an automated technique for robustly and rapidly detecting 3D axonal structure. In this paper, we present a pure 3D approach to extract the curvilinear structure of axonal axes from microscopic image stacks. The method mimics the axon tracing procedure in 3D space as walking along a path with minimized cost value, which corresponds to the shortest path problem (SPP) in graph theory. The global solution for SPP, such as Dijkstra's algorithm, is infeasible for the real axon tracing problem because of the computation cost. We simplify this problem using a dynamic local tracing technique with linear computation complexity. The merits of the proposed method lie in that it can handle the short turn and non-vertical problems and also can separate closely distributed axons from each other

[1]  D. Aykac,et al.  Segmentation and analysis of the human airway tree from three-dimensional X-ray CT images , 2003, IEEE Transactions on Medical Imaging.

[2]  Milan Sonka,et al.  Intrathoracic airway trees: segmentation and airway morphology analysis from low-dose CT scans , 2005, IEEE Transactions on Medical Imaging.

[3]  Stephen T. C. Wong,et al.  Shape-constrained repulsive snake method to segment and track neurons in 3D microscopy images , 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

[4]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Andrea Remuzzi,et al.  Computational Geometry for Patient-Specific Reconstruction and Meshing of Blood Vessels from Angiography , 2003, IEEE Trans. Medical Imaging.

[6]  N. Kasthuri,et al.  The role of neuronal identity in synaptic competition , 2003, Nature.

[7]  Stephen T. C. Wong,et al.  Repulsive force based snake model to segment and track neuronal axons in 3D microscopy image stacks , 2006, NeuroImage.

[8]  K. Koffka.  Principles Of Gestalt Psychology , 1936 .

[9]  Ronald L. Rivest,et al.  Introduction to Algorithms, Second Edition , 2001 .

[10]  L. Antiga,et al.  Computational geometry for patient-specific reconstruction and meshing of blood vessels from MR and CT angiography , 2003, IEEE Transactions on Medical Imaging.

[11]  B. Silverman.  Density estimation for statistics and data analysis , 1986 .

[12]  Ronald L. Rivest,et al.  Introduction to Algorithms , 1990 .

[13]  Michael Scholz,et al.  New methods for the computer-assisted 3-D reconstruction of neurons from confocal image stacks , 2004, NeuroImage.