Directional multiscale representations and applications in digital neuron reconstruction

Recent advances in the field of multiscale representations have spurred the emergence of a new generation of powerful techniques for the efficient analysis of images and other multidimensional data. These novel techniques enable the quantification of essential geometric characteristics in complex im...

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Bibliographic Details
Published in:Journal of computational and applied mathematics 2019-03, Vol.349, p.482-493
Main Authors: Kayasandik, Cihan, Guo, Kanghui, Labate, Demetrio
Format: Article
Language:English
Subjects:
Fluorescent microscopy
Multiscale analysis
Neuron profiling
Neuron reconstruction
Sparse representations
Wavelets
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Summary:Recent advances in the field of multiscale representations have spurred the emergence of a new generation of powerful techniques for the efficient analysis of images and other multidimensional data. These novel techniques enable the quantification of essential geometric characteristics in complex imaging data resulting in improved algorithms for image restoration, feature extraction and classification. We discuss the application of these ideas in neuroscience imaging and describe a novel method for the accurate and efficient identification of cellular bodies of neurons in multicellular images. This method is instrumental to the design of a novel algorithm for neuronal tracing.
ISSN:0377-0427
1879-1778
DOI:10.1016/j.cam.2018.09.003