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Cancer Research
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利用傅里叶变换和自组织映射的形态学区分健康和病理细胞
JoVE Journal
Cancer Research
This content is Free Access.
JoVE Journal
Cancer Research
Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps
Please note that all translations are automatically generated.
Click here for the English version.
利用傅里叶变换和自组织映射的形态学区分健康和病理细胞
DOI:
10.3791/58543-v
•
08:59 min
•
October 28, 2018
•
Fabian L. Kriegel
2
,
Ralf Köhler
,
Jannike Bayat-Sarmadi
,
Simon Bayerl
,
Anja E. Hauser
3
,
Raluca Niesner
,
Andreas Luch*
1
,
Zoltan Cseresnyes*
4
1
Department of Chemical and Product Safety
,
German Federal Institute for Risk Assessment (BfR)
,
2
Deutsches Rheuma-Forschungszentrum (DRFZ) Berlin, a Leibniz Institute
,
3
Charité Universitätsmedizin Berlin
,
4
Applied Systems Biology
,
Leibniz Institute for Natural Product Research and Infection Biology Hans Knöll Institute
Chapters
00:04
Title
01:11
Reconstruct the 3D Image
03:13
Transform the 3D Reconstructed Surfaces into 2D Projections
04:28
Find the Periphery and Calculate the Fourier Components using Fiji
05:13
Self-Organizing Maps
06:53
Results: Robustness of SOM Mapping Approach
08:32
Conclusion
Summary
Automatic Translation
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Automatic Translation
在这里, 我们提供了一个工作流, 可以根据其3维形状识别健康和病理细胞。我们描述了使用基于3D 表面的2D 投影轮廓的过程来训练自组织地图, 该图将提供调查的细胞种群的客观聚类。
Tags
Morphology-based Distinction
Fourier Transforms
Self-organizing Maps
3D Microscopy
Cell Reconstruction
Surface Creation
Smoothing
Thresholding
Cancer Research
Immunology
Diagnosis
Therapy
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