Imaging is crucial in the multidisciplinary approach to head and neck cancer management. The rapid technological development of recent years makes it necessary for all members of the multidisciplinary
1 Introduction2 Representatives2.1 Representative of data sets with one feature2.1.1 Best LS-representativ2.1.2 Best 1-representative2.1.3 Best representative of weighted data2.1.4 Bregman divergences2.2 Representative of data sets with two features2.2.1 Fermat-Torricelli-Weber problem2.2.2 Centroid of a set in the plane2.2.3 Median of a set in the plane 2.2.4 Geometric median of a set in the plane2.3 Representative of data sets with several features2.3.1 Representative of weighted data2.4 Representative of periodic data2.4.1 Representative of data on the unit circle2.4.2 Burn diagram3 Data clustering3.1 Optimal k-partition3.1.1 Minimal distance principle and Voronoi diagram3.1.2 k-means algorithm3.2 Clustering data with one feature3.2.1 Application of the LS-distance-like function3.2.2 The dual problem3.2.3 Least absolute deviation principle3.2.4 Clustering weighted data3.3 Clustering data with two or several features3.3.1 Least squares principle3.3.2 The dual problem3.3.3 Least absol
