D-LMBmap: a fully automated deep-learning pipeline for whole-brain profiling of neural circuitry

Recent proliferation and integration of tissue-clearing methods and light-sheet fluorescence microscopy has created new opportunities to achieve mesoscale three-dimensional whole-brain connectivity mapping with exceptionally high throughput. With the rapid generation of large, high-quality imaging d...

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Veröffentlicht in:	Nature methods Jg. 20; H. 10; S. 1593 - 1604
Hauptverfasser:	Li, Zhongyu, Shang, Zengyi, Liu, Jingyi, Zhen, Haotian, Zhu, Entao, Zhong, Shilin, Sturgess, Robyn N., Zhou, Yitian, Hu, Xuemeng, Zhao, Xingyue, Wu, Yi, Li, Peiqi, Lin, Rui, Ren, Jing
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Nature Publishing Group US 01.10.2023 Nature Publishing Group
Schlagworte:	631/1647/245 631/378 Algorithms Annotations Automation Bioinformatics Biological Microscopy Biological Techniques Biomedical and Life Sciences Biomedical Engineering/Biotechnology Brain Brain Mapping Circuits Computational neuroscience Data analysis Deep Learning Fluorescence microscopy Image Processing, Computer-Assisted - methods Image segmentation Laser microscopy Learning Life Sciences Light sheets Machine learning Mapping Mesoscale phenomena Modules Neural networks Neuroimaging Proteomics Segmentation Workflow
ISSN:	1548-7091, 1548-7105, 1548-7105
Online-Zugang:	Volltext
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