Abstract:We present an object-oriented library for the systematic training, testing and benchmarking of classification algorithms for computer-assisted diagnosis tasks, with a focus on tumor probability estimation from magnetic resonance spectroscopy imaging (MRSI) measurements. In connection with a graphical user interface for data annotation, it allows clinical end users to flexibly adapt these classifiers towards changed classification tasks, to benchmark various classifiers and preprocessing steps and to perform qu… Show more
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