Academic Journal of Computing & Information Science, 2020, 3(5); doi: 10.25236/AJCIS.2020.030504.
School of Control and Computer Engineering, North China Electric Power University, Baoding 071003, Hebei, China
The tortuosity of corneal nerve fibres is correlated with a number of diseases such as diabetic neuropathy. The assessment of corneal nerve tortuosity in in vivo confocal microscopy images can inform the detection of diseases and complications. Clustering is a typical technique which is often used to discover data distribution. This paper proposes a dominant set based fuzzy clustering ensemble method based on cluster filtering. The proposed method uses similarity relationship to represent the connections among the clusters to form a graph and the dominant sets are extracted to form meta-clusters. Then, each meta-cluster is aggregated to obtain a cluster in the final clustering ensemble outputs. Experimental results on a public corneal nerve tortuosity data set demonstrates the effectiveness of the proposed method in IVCM image tortuosity grading.
clustering ensemble, fuzzy clustering, dominant set, nerve tortuosity
Pan Su. Dominant Set Based Fuzzy Clustering Ensemble for Aggregation of Tortuosity Measures. Academic Journal of Computing & Information Science (2020), Vol. 3, Issue 5: 23-30. https://doi.org/10.25236/AJCIS.2020.030504.
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