Segmentation of abnormal liver region based on earth movers distance between histograms with mapping of the distances by multidimensional scaling
In this paper, we propose using earth movers distance (EMD) to obtain the appropriate similarity between each histogram for segmentation of abnormal liver regions with mapping of the distances by multidimensional scaling. Conventionally, the similarity between each histogram is calculated by integrating the difference between each bin of the histograms. However, this similarity is unsuitable for appropriate comparison of the histograms because the number of bins for calculating the local histograms of computed tomography images varies. We used EMD to resolve this problem regarding the difference in bin numbers, and the obtained distances are used for mapping the local histograms by multidimensional scaling to low-dimensional space. In the low-dimensional space, the abnormal liver region was well segmented by support vector machine in the test datasets.
earth movers distance histogram multidimensional scaling support vector machine