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Clustering of non-convex patterns for medical imaging

The study treats the problem of partitional clustering of non-convex patterns of arbitrary shape, with no definite analytical description of the data. A new method for calculating the distance is defined, according to a data induced metric principle. Calculation of the distance is carried out using weighted graphs. The new distance is introduced in the fuzzy k-means algorithm, and the modified fuzzy k-means algorithm is tested on synthetic data, and on MRI images of the heart.