Siemens Medical Solutions Usa, Inc.

Bernd Wachmann

Claus Neubauer

Jie Cheng

Chao Yuan

Thomas Fuchs

Disclosed is a technique for classifying tissue based on image data. A plurality of tissue parameters are extracted from image data (e.g., magnetic resonance image data) to be classified. The parameters are preprocessed, and the tissue is classified using a classification algorithm and the preprocessed parameters. In one embodiment, the parameters are preprocessed by discretization of the parameters. The classification algorithm may use a decision model for the classification of the tissue, and the decision model may be generated by performing a machine learning algorithm using preprocessed tissue parameters in a training set of data. In one embodiment, the machine learning algorithm generates a Bayesian network. The image data used may be magnetic resonance image data that was obtained before and after the intravenous administration of lymphotropic superparamagnetic nanoparticles.

Method and apparatus for classifying tissue using image data

A method for analyzing biological data includes classifying a first set of biological data in a first classifier, classifying a second set of biological data in a second classifier, combining the results of the first classifier with the results of the second classifier, and analyzing the results as a function of the similarity measure of the first classifier and the similarity measure of the second classifier.

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Lawrenceville, NJ, United States of America

Bernd Wachmann