A Broadly Applicable 3-D Neuron Tracing Method Based on Open-Curve Snake

Abstract

This paper presents a broadly applicable algorithm and a comprehensive open-source software implementation for automated tracing of neuronal structures in 3-D microscopy images. The core 3-D neuron tracing algorithm is based on three-dimensional (3-D) open-curve active Contour (Snake). It is initiated from a set of automatically detected seed points. Its evolution is driven by a combination of deforming forces based on the Gradient Vector Flow (GVF), stretching forces based on estimation of the fiber orientations, and a set of control rules. In this tracing model, bifurcation points are detected implicitly as points where multiple snakes collide. A boundariness measure is employed to allow local radius estimation. A suite of pre-processing algorithms enable the system to accommodate diverse neuronal image datasets by reducing them to a common image format. The above algorithms form the basis for a comprehensive, scalable, and efficient software system developed for confocal or brightfield images. It provides multiple automated tracing modes. The user can optionally interact with the tracing system using multiple view visualization, and exercise full control to ensure a high quality reconstruction. We illustrate the utility of this tracing system by presenting results from a synthetic dataset, a brightfield dataset and two confocal datasets from the DIADEM challenge.

Automated analysis of spine dynamics on live CA1 pyramidal cells

“…This was a useful feature for our application, but it prevented fully automatic analysis and batch processing. Sophisticated algorithms for automatic backbone reconstruction of neurons in fluorescence images have been developed (González et al, 2009;Wang et al, 2011;Chothani et al, 2011), and the Diadem challenge provides a useful benchmarking procedure for this computational problem. Similar to the processing of time series, it would be feasible to initialize our spine detection software with the result of a dendrite tracing algorithm.…”

Three-dimensional neurite tracing under globally varying contrast

“…In both cases, we made comparisons with three DIADEM challenge finalists, namely the neuron circuit tracer (NCT) [4], the principal curve tracing (PCT) [1], and the 3D snake model in [11], using the metric in [6]. Due to space limitation we cannot include here numerical comparisons.…”

“…There is a large number of neurite reconstruction approaches, many of which have been reviewed in [8] and [11]. They can be categorized into global, local, and combinations of the two.…”

“…Such methods involve, in general, measuring vesselness, e.g., [5], binarization, and/or skeletonization, as in [12]. Local methods extract the neurite centerline by starting from seeds, which are located automatically or manually, and iteratively perform tracing based on intensity statistics [10,9,11]. Although most of these methods have been shown to perform This work is supported by NSF/DBI [#1252597]: 'CAREER: Modeling the structure and dynamics of neuronal circuits in the Drosophila larvae using image analytics' awarded to G. Tsechpenakis.…”

“…We validate our method using two different types of data: sensory neurons from larva Drosophila, and different datasets from the DIADEM challenge 1 [2]. Here we compare our method with three of the DIADEM challenge finalists, namely the neural circuit tracer [4], the principle curve tracing [1], and the 3D snake model in [11].…”