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Updated: Jun 12, 2025

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
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Extended Quality (eQual): Radial Threshold Clustering Based on n-ary Similarity.

Lexin Chen1,2, Micah Smith3, Daniel R Roe4

  • 1Department of Chemistry, University of Florida, Gainesville, Florida 32611, United States.

Journal of Chemical Information and Modeling
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Summary

We optimized Radial Threshold Clustering (RTC) into Extended Quality Clustering (eQual), an O(N) algorithm. This new method offers faster, more consistent frame clustering, improving efficiency for large datasets.

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Area of Science:

  • Computational science
  • Data science
  • Algorithm development

Background:

  • Radial Threshold Clustering (RTC) is an O(N^2) partitioning algorithm for grouping similar frames.
  • RTC suffers from inefficiency with large datasets and order-dependent results during ties.
  • Existing clustering methods may lack scalability and consistency.

Purpose of the Study:

  • To transform the O(N^2) Radial Threshold Clustering (RTC) algorithm into an efficient O(N) algorithm named Extended Quality Clustering (eQual).
  • To enhance clustering by improving speed and ensuring order-invariant results.
  • To produce more compact and distinct clusters.

Main Methods:

  • Implemented k-means++ for faster seed selection in frame clustering.
  • Introduced extended similarity indices to select the densest and most compact cluster, ensuring order invariance.
  • Developed Extended Quality Clustering (eQual) with a linear time complexity.

Main Results:

  • Achieved O(N) time complexity, significantly improving efficiency over RTC's O(N^2).
  • Ensured clustering results are invariant to the order of input frames.
  • Demonstrated the generation of more compact and well-separated clusters.

Conclusions:

  • Extended Quality Clustering (eQual) provides a scalable and consistent alternative to Radial Threshold Clustering (RTC).
  • The enhanced algorithm addresses key limitations of RTC, offering improved performance and reliability.
  • eQual is suitable for large-scale frame clustering tasks requiring efficiency and robust results.