Using MapReduce for Large–scale Medical Image Analysis

The growth of the amount of medical image data produced on a daily basis in modern hospitals forces the adaptation of traditional medical image analysis and indexing approaches towards scalable solutions. In this work, MapReduce is used to speed up and make possible three large–scale medical image processing use–cases: (i) parameter optimization for lung texture classification using support vector machines (SVM), (ii) content–based medical image indexing, and (iii) three–dimensional directional wavelet analysis for solid texture classification.