Author
Listed:
- Rui Li
(Xiamen University
University of Southern California
Central China Normal University)
- Muye Zhu
(University of Southern California)
- Junning Li
(University of Southern California
Intuitive Surgical Inc.)
- Michael S. Bienkowski
(University of Southern California)
- Nicholas N. Foster
(University of Southern California)
- Hanpeng Xu
(University of Southern California)
- Tyler Ard
(University of Southern California)
- Ian Bowman
(University of Southern California)
- Changle Zhou
(Xiamen University)
- Matthew B. Veldman
(University of California at Los Angeles
David Geffen School of Medicine at UCLA)
- X. William Yang
(University of California at Los Angeles
David Geffen School of Medicine at UCLA)
- Houri Hintiryan
(University of Southern California)
- Junsong Zhang
(Xiamen University
Central China Normal University)
- Hong-Wei Dong
(University of Southern California
University of Southern California
University of Southern California)
Abstract
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.
Suggested Citation
Rui Li & Muye Zhu & Junning Li & Michael S. Bienkowski & Nicholas N. Foster & Hanpeng Xu & Tyler Ard & Ian Bowman & Changle Zhou & Matthew B. Veldman & X. William Yang & Houri Hintiryan & Junsong Zhan, 2019.
"Precise segmentation of densely interweaving neuron clusters using G-Cut,"
Nature Communications, Nature, vol. 10(1), pages 1-12, December.
Handle:
RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-09515-0
DOI: 10.1038/s41467-019-09515-0
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