Run Particle Clustering » History » Version 4
Anke Mulder, 05/18/2010 02:15 PM
| 1 | 1 | Anke Mulder | h1. Run Particle Clustering |
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| 3 | 2 | Anke Mulder | After interimage variance analysis and data reduction procedures done via feature analysis, particles are ordered and summed according to their relative similarity (proximity in reduced multidimensional image point space). Traditional methods include k-means and hierarchical ascendant classification (_Frank et. al Journal of Microscopy v150,99-115 (1988))._ |
| 4 | h2. Particle Clustering Procedures |
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| 6 | 2 | Anke Mulder | # [[Hierarchical or K-means Clustering]] |
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| 11 | ______ |
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| 13 | 4 | Anke Mulder | [[<Run Alignment|Run Alignment]] | [[Run Feature Analysis|Run Feature Analysis >]] |
| 14 | 1 | Anke Mulder | |
| 15 | ______ |