2F23 Quantitative analysis of trajectory data during cell aggregate formation

2014 ◽  
Vol 2014.26 (0) ◽  
pp. 491-492
Author(s):  
Akihisa OTAKA ◽  
Kenji ISSHIKI ◽  
Kumpei SANO ◽  
Katsura KOJIMA ◽  
Yasushi TAMADA ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
Cell Aggregate ◽  
Aggregate Formation ◽  
Trajectory Data

Fibronectin regulates anoikis resistance via cell aggregate formation

2021 ◽  
Author(s):  
Hyeong-jun Han ◽  
Jee Young Sung ◽  
Su-Hyeon Kim ◽  
Un-Jung Yun ◽  
Hyeryeong Kim ◽  
...  
Keyword(s):  
Cell Aggregate ◽  
Aggregate Formation ◽  
Anoikis Resistance

Rapid and Versatile Cell Aggregate Formation Using Lipid-Conjugated Heparin

2018 ◽  
Vol 10 (29) ◽  
pp. 24431-24439 ◽  
Author(s):  
Eunsol Kim ◽  
Jong Chul Kim ◽  
Kiyoon Min ◽  
MeeiChyn Goh ◽  
Giyoong Tae
Keyword(s):  
Cell Aggregate ◽  
Aggregate Formation

A microwell pattern for C17.2 cell aggregate formation with concave cylindrical surface induced cell peeling

Biomaterials ◽  
2014 ◽  
Vol 35 (35) ◽  
pp. 9423-9437 ◽  
Author(s):  
Li-Guang Zhang ◽  
Dong-Huo Zhong ◽  
Yiguo Zhang ◽  
Chen-Zhong Li ◽  
William S. Kisaalita ◽  
...  
Keyword(s):  
Cylindrical Surface ◽  
Cell Aggregate ◽  
Aggregate Formation

scholarly journals Research on Long Jump Posture in School Physical Education Teaching Based on Video Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Tianchang He ◽  
Danyang Lv ◽  
Zehao Li
Keyword(s):  
Quantitative Analysis ◽  
Physical Education ◽  
Video Analysis ◽  
Video Processing ◽  
Human Movement ◽  
Video Data ◽  
Trajectory Data ◽  
Processing Technologies ◽  
Long Jump ◽  
Skill Improvement

Based on video, the human movement can be analyzed to achieve scientific training and skill improvement. Specifically, according to the video data during the movement, the human body can be detected and tracked, and relevant trajectory data can be obtained. On this basis, key motion parameters can be obtained and quantitative analysis of motion can be achieved. This paper uses video processing technologies to analyze the long jump posture in physical education. According to the video sequences measured during the athlete’s long jump, the target detection and tracking algorithms are used to obtain the athlete’s trajectory after preprocessing. Afterwards, further processing is carried out to calculate speed, angle, posture, and other related information to assist scientific sports training. The experimental results based on the measured data show that the algorithm can realize the analysis of the long jump scene and complete the quantitative analysis of the key indicators of the athletes. The research results can effectively support school physical education and guidance training and also provide a reference for other competitive video analysis.

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