Wisconsin Alumni Research Foundation

Medical Imaging
Medical Imaging
Determining A Class Type Of A Sample By Clustering Locally Optimal Model Parameters
WARF: P150082US02

Inventors: Amos Ron, Shengnan Wang


The Invention
A method for characterizing a sample includes acquiring a trace signal for the sample. A set of configurations is generated for defining modeling signals to model the trace signal. Each modeling signal is defined by a plurality of model parameters, and each configuration represents an associated modeling signal having a locally optimal score for fitting the trace signal. A classification cluster is defined in a parameter domain defined by the plurality of model parameters. The classification cluster has an associated class type. The sample is determined to have the class type associated with the classification cluster responsive to determining that at least one of the configurations in the set has a distance from the classification cluster less than a threshold.
Additional Information
For More Information About the Inventors
For current licensing status, please contact Jeanine Burmania at [javascript protected email address] or 608-960-9846

WARF