| 摘要 |
A method, computer program product, and data processing system for building a training set and classifier model for tissue classification from MRI images using limited training data are disclosed. In a preferred embodiment, the method begins with a given set of multispectral MRI scans of an abdominal slice of a human organ. A clustering algorithm is applied to the image data to cluster different objects in the image into unique clusters. A deterministic initialization procedure is applied to the clustering algorithm to ensure solution uniqueness, convergence, and the creation of meaningful clusters. A human domain expert then produces a corrected set of clusters by retaining only clusters of interest. A training set is generated that represents samples of each of the tissue types of interest, as well as a validation set. One or more classifiers are constructed from the training set and then evaluated for accuracy using the validation set.
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