Three-dimensional neurite tracing under globally varying contrast

Gulyanon, Sarun; Sharifai, N.; Bleykhman, S.; Kelly, Edward F.; Kim, Michael D.; Chiba, Akira; Tsechpenakis, Gavriil

doi:10.1109/isbi.2015.7164010

Cited by 10 publications

(2 citation statements)

References 13 publications

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“…Other programs/methods such as the use of deformable models have also been used in some studies e.g., in the three-dimensional tracing of neurites. 11,12 We speculate that these methods would be equally competent for image analysis of acellular capillaries, however, these methods are much more computationally intensive than the one described in this manuscript.…”

Section: Discussionmentioning

confidence: 90%

Automated computer-based enumeration of acellular capillaries for assessment of diabetic retinopathy

Tüceryan

Hemmady

Schebler

et al. 2020

Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging

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Diabetic retinopathy (DR) is the most common complications of diabetes; if untreated the DR can lead to a vision loss. The treatment options for DR are limited and the development of newer therapies are of considerable interest. Drug screening for the retinopathy treatment is undertaken using animal models in which the quantification of acellular capillaries (capillary without any cells) is used as a marker to assess the severity of retinopathy and the treatment response. The traditional approach to quantitate acellular capillaries is through manual counting. The purpose of this investigation was to develop an automated technique for the quantitation of acellular capillaries using computer-based image processing algorithms. We developed a custom procedure using the Python, the medial axis transform (MAT) and the connected component algorithm. The program was tested on the retinas of wild-type and diabetic mice and the results were compared to single blind manual counts by two independent investigators. The program successfully identified and enumerated acellular capillaries. The acellular capillary counts were comparable to the traditional manual counting. In conclusion, we developed an automated computer-based program, which can be effectively used for future pharmacological development of treatments for DR. This algorithm will enhance consistency in retinopathy assessment and reduce the time for analysis, thus, contributing substantially towards the development of future pharmacological agents for the treatment of DR.

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Section: Discussionmentioning

confidence: 90%

Automated computer-based enumeration of acellular capillaries for assessment of diabetic retinopathy

Tüceryan

Hemmady

Schebler

et al. 2020

Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging

View full text Add to dashboard Cite

show abstract

“…Researchers have developed a variety of methods for the reconstruction of LM and EM images [10,37,54]. Generally, from the original 2D microscopy images to the 3D morphological data, a neuron tracing system consists of several processing steps, including image preprocessing (e.g., noise reduction, deconvolution, mosaicing), segmentation (e.g., soma, dendritic trees, spines, axons segmentation), reconstruction and connection ( [5,31,52,16,62,11,18]). Fig.…”

Section: D Neuron Morphologymentioning

confidence: 99%

Interactive Exploration for Continuously Expanding Neuron Databases

Metaxas

et al. 2017

Methods

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This paper proposes a novel framework to help biologists explore and analyze neurons based on retrieval of data from neuron morphological databases. In recent years, the continuously expanding neuron databases provide a rich source of information to associate neuronal morphologies with their functional properties. We design a coarse-to-fine framework for efficient and effective data retrieval from large-scale neuron databases. In the coarse-level, for efficiency in large-scale, we employ a binary coding method to compress morphological features into binary codes of tens of bits. Short binary codes allow for real-time similarity searching in Hamming space. Because the neuron databases are continuously expanding, it is inefficient to re-train the binary coding model from scratch when adding new neurons. To solve this problem, we extend binary coding with online updating schemes, which only considers the newly added neurons and update the model on-the-fly, without accessing the whole neuron databases. In the fine-grained level, we introduce domain experts/users in the framework, which can give relevance feedback for the binary coding based retrieval results. This interactive strategy can improve the retrieval performance through re-ranking the above coarse results, where we design a new similarity measure and take the feedback into account. Our framework is validated on more than 17,000 neuron cells, showing promising retrieval accuracy and efficiency. Moreover, we demonstrate its use case in assisting biologists to identify and explore unknown neurons.

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Automated 3D Soma Segmentation with Morphological Surface Evolution for Neuron Reconstruction

et al. 2018

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The automatic neuron reconstruction is important since it accelerates the collection of 3D neuron models for the neuronal morphological studies. The majority of the previous neuron reconstruction methods only focused on tracing neuron fibres without considering the somatic surface. Thus, topological errors often present around the soma area in the results obtained by these tracing methods. Segmentation of the soma structures can be embedded in the existing neuron tracing methods to reduce such topological errors. In this paper, we present a novel method to segment the soma structures with complex geometry. It can be applied along with the existing methods in a fully automated pipeline. An approximate bounding block is firstly estimated based on a geodesic distance transform. Then the soma segmentation is obtained by evolving the surface with a set of morphological operators inside the initial bounding region. By evaluating the methods against the challenging images released by the BigNeuron project, we showed that the proposed method can outperform the existing soma segmentation methods regarding the accuracy. We also showed that the soma segmentation can be used for enhancing the results of existing neuron tracing methods.

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Three-dimensional neurite tracing under globally varying contrast

Cited by 10 publications

References 13 publications

Automated computer-based enumeration of acellular capillaries for assessment of diabetic retinopathy

Automated computer-based enumeration of acellular capillaries for assessment of diabetic retinopathy

Interactive Exploration for Continuously Expanding Neuron Databases

Automated 3D Soma Segmentation with Morphological Surface Evolution for Neuron Reconstruction

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