Directional multiscale representations and applications in digital neuron reconstruction

被引:3
作者
Kayasandik, Cihan [2 ]
Guo, Kanghui [1 ]
Labate, Demetrio [2 ]
机构
[1] Missouri State Univ, Dept Math, Springfield, MO USA
[2] Univ Houston, Dept Math, Houston, TX 77204 USA
基金
美国国家科学基金会;
关键词
Fluorescent microscopy; Multiscale analysis; Neuron profiling; Neuron reconstruction; Sparse representations; Wavelets; MORPHOLOGY; IMAGES; ALGORITHMS; FRAMES;
D O I
10.1016/j.cam.2018.09.003
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
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. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:482 / 493
页数:12
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