Regularized color clustering in medical image database

C. H. Li*, Pong Chi YUEN

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

65 Citations (Scopus)


A regularized color clustering algorithm is proposed to solve the color clustering problem in medical image database. By incorporating both measures of cluster separability and cluster compactness, regularized color clustering allows the automatic extraction of significant color groups with varying populations. Experimental results in different color spaces show that the regularized color clustering gives superior results in extracting significant distinct/abnormal color clusters without significant increases in cluster compactness. Furthermore, results of color clustering in different color spaces show that the LUV color space is more suitable for color clustering. Methods for selecting the regularization constants have also been suggested.

Original languageEnglish
Pages (from-to)1150-1155
Number of pages6
JournalIEEE Transactions on Medical Imaging
Issue number11
Publication statusPublished - Nov 2000

Scopus Subject Areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering


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