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Developmental Biology
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基于神经网络的发育能力或不称职小鼠全生长卵母细胞的识别
JoVE Journal
Developmental Biology
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JoVE Journal
Developmental Biology
A Neural Network-Based Identification of Developmentally Competent or Incompetent Mouse Fully-Grown Oocytes
Please note that all translations are automatically generated.
Click here for the English version.
基于神经网络的发育能力或不称职小鼠全生长卵母细胞的识别
DOI:
10.3791/56668-v
•
10:04 min
•
March 03, 2018
•
Federica Cavalera
,
Mario Zanoni
,
Valeria Merico
,
Thi Thu Hien Bui
2
,
Martina Belli
3
,
Lorenzo Fassina
,
Silvia Garagna
,
Maurizio Zuccotti
1
Laboratorio di Biologia dello Sviluppo, Dipartimento di Biologia e Biotecnologie “Lazzaro Spallanzani”
,
University of Pavia
,
2
Institute of Biotechnology
,
University of Helsinki
,
3
Department of Reproductive Medicine
,
University of California San Diego
,
4
Dipartimento di Ingegneria Industriale e dell’Informazione
,
University of Pavia
Chapters
00:00
Title
00:14
Introduction
02:03
Cumulus Oocyte Complex isolation
03:25
Oocyte classification with fluorochrome Hoechst 33342
04:56
Neural network-based oocyte classification
06:12
Results
09:38
Conclusion
Summary
Automatic Translation
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Automatic Translation
在这里, 我们提出了一个非侵入性评估的卵母细胞发育能力在他们的
体外
成熟从生发泡到中期 II 阶段。该方法将时间推移成像与粒子图像测速 (PIV) 和神经网络分析相结合。
Tags
Neural Network
Oocyte Identification
Developmental Competence
Particle Image Velocimetry
Time-lapse Imaging
In Vitro Maturation
Germinal Vesicle
Metaphase II
Infertility
Premature Ovarian Failure
Non-invasive Procedure
Ovary
Cumulus Cells
Hoechst 33342
Article
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