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Journal
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Neuroscience
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两种算法的高通量和多参数定量<em>果蝇</em>神经肌肉接头形态
JoVE Journal
Neuroscience
This content is Free Access.
JoVE Journal
Neuroscience
Two Algorithms for High-throughput and Multi-parametric Quantification of
Drosophila
Neuromuscular Junction Morphology
Please note that all translations are automatically generated.
Click here for the English version.
两种算法的高通量和多参数定量<em>果蝇</em>神经肌肉接头形态
DOI:
10.3791/55395-v
•
12:29 min
•
May 03, 2017
•
Anna Castells-Nobau*
1
,
Bonnie Nijhof*
1
,
Ilse Eidhof
,
Louis Wolf
,
Jolanda M. Scheffer-de Gooyert
,
Ignacio Monedero
4
,
Laura Torroja
,
Jeroen A.W.M. van der Laak
5
,
Annette Schenck*
1
1
Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour
,
Radboud University Medical Center
,
2
Microscopical Imaging Centre (MIC)
,
Radboud University Medical Center
,
3
Department of Biology
,
Universidad Autónoma de Madrid
,
4
Department of Clinical and Experimental Medicine
,
Linköping University
,
5
Department of Pathology
,
Radboud University Medical Center
Chapters
00:05
Title
01:03
Creating NMJ Images with Defined Features
04:50
Macro Settings: Rolling Ball Radius Value and Auto-threshold
07:26
Macro Settings: Maxima Noise Tolerance Value, and Brp-puncta Thresholds
10:16
Results: Validating the Marco by Recapitulating Known NMJ Defects
11:38
Conclusion
Summary
Automatic Translation
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Automatic Translation
两个图像分析算法,“
果蝇
NMJ形态特征”和“
果蝇
NMJ布顿形态特征”
被创建
,以自动量化
果蝇
神经肌肉接头(NMJ)九个形态特征。
Tags
Drosophila
Neuromuscular Junction
Morphology
Quantification
High-throughput
Multi-parametric
Image Analysis
Macros
DLG1
BRP
ROI
Automated Analysis
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