Precise segmentation of densely interweaving neuron clusters using G-Cut.

التفاصيل البيبلوغرافية
العنوان:	Precise segmentation of densely interweaving neuron clusters using G-Cut.
المؤلفون:	Li R; Fujian Key Laboratory of Brain-Inspired Computing Technique and Applications, Department of Cognitive Science, School of Informatics, Xiamen University, Xiamen, 361005, China.; Center for Integrative Connectomics, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, 90095, USA.; National Engineering Research Center for E-Learning, Central China Normal University, 430079, Wuhan, China., Zhu M; Center for Integrative Connectomics, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, 90095, USA., Li J; Center for Integrative Connectomics, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, 90095, USA.; Intuitive Surgical Inc., 1020 Kifer Road, Sunnyvale, CA, 94086, USA., Bienkowski MS; Center for Integrative Connectomics, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, 90095, USA., Foster NN; Center for Integrative Connectomics, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, 90095, USA., Xu H; Center for Integrative Connectomics, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, 90095, USA., Ard T; Laboratory of Neuroimaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, 90095, USA., Bowman I; Center for Integrative Connectomics, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, 90095, USA., Zhou C; Fujian Key Laboratory of Brain-Inspired Computing Technique and Applications, Department of Cognitive Science, School of Informatics, Xiamen University, Xiamen, 361005, China., Veldman MB; Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, CA, 90095, USA.; Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA., Yang XW; Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, CA, 90095, USA.; Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA., Hintiryan H; Center for Integrative Connectomics, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, 90095, USA., Zhang J; Fujian Key Laboratory of Brain-Inspired Computing Technique and Applications, Department of Cognitive Science, School of Informatics, Xiamen University, Xiamen, 361005, China. jszhang@outlook.com.; National Engineering Research Center for E-Learning, Central China Normal University, 430079, Wuhan, China. jszhang@outlook.com., Dong HW; Center for Integrative Connectomics, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, 90095, USA. hongwei.dong@loni.usc.edu.; Zilkha Neurogenetic Institute, University of Southern California, Los Angeles, CA, 90095, USA. hongwei.dong@loni.usc.edu.; Department of Neurology, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, 90095, USA. hongwei.dong@loni.usc.edu.
المصدر:	Nature communications [Nat Commun] 2019 Apr 04; Vol. 10 (1), pp. 1549. Date of Electronic Publication: 2019 Apr 04.
نوع المنشور:	Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
اللغة:	English
بيانات الدورية:	Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101528555 Publication Model: Electronic Cited Medium: Internet ISSN: 2041-1723 (Electronic) Linking ISSN: 20411723 NLM ISO Abbreviation: Nat Commun Subsets: MEDLINE
أسماء مطبوعة:	Original Publication: [London] : Nature Pub. Group
مواضيع طبية MeSH:	Computer Simulation* , Nerve Net, Brain Mapping/methods , Neurons/*cytology, Algorithms ; Computational Biology ; Models, Theoretical ; Neurons/ultrastructure
مستخلص:	Characterizing the precise three-dimensional morphology and anatomical context of neurons is crucial for neuronal cell type classification and circuitry mapping. Recent advances in tissue clearing techniques and microscopy make it possible to obtain image stacks of intact, interweaving neuron clusters in brain tissues. As most current 3D neuronal morphology reconstruction methods are only applicable to single neurons, it remains challenging to reconstruct these clusters digitally. To advance the state of the art beyond these challenges, we propose a fast and robust method named G-Cut that is able to automatically segment individual neurons from an interweaving neuron cluster. Across various densely interconnected neuron clusters, G-Cut achieves significantly higher accuracies than other state-of-the-art algorithms. G-Cut is intended as a robust component in a high throughput informatics pipeline for large-scale brain mapping projects.
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معلومات مُعتمدة:	R01 MH094360 United States MH NIMH NIH HHS; U01 CA198932 United States CA NCI NIH HHS; U01 MH106008 United States MH NIMH NIH HHS
تواريخ الأحداث:	Date Created: 20190406 Date Completed: 20190501 Latest Revision: 20240715
رمز التحديث:	20240715
مُعرف محوري في PubMed:	PMC6449501
DOI:	10.1038/s41467-019-09515-0
PMID:	30948706
قاعدة البيانات:	MEDLINE

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تدمد:	2041-1723
DOI:	10.1038/s41467-019-09515-0