System and method for joint optimization of cascaded...

Details System and method for joint optimization of cascaded... System and method for joint optimization of cascaded...

2011-06-14

2011-06-14

Vincent, David R (Department: 2129)

Data processing: artificial intelligence

Neural network

Learning task

C382S118000, C382S103000

Reexamination Certificate

active

07962428

ABSTRACT:
A method for training classifiers for Computer-Aided Detection in medical images includes providing an image feature training set {(xi, yi)}i=1l, wherein xiεRdare input feature variables and yiε{−1,1} are class labels, and a cascade of K classifiers to be trained, minimizing, for each classifier k, a first cost function to initialize an αk0associated with each classifier k, fixing all classifiers except classifier k and minimizing a second cost function to solve for αkcfor a counter value c using the training dataset {(xik, yi)}i=1l, calculating a third cost function Jc(αlc, . . . , αKc) for each classifier k, and comparing Jcwith a previous iteration Jc−1, wherein if Jc−Jc−1is less than a predetermined tolerance, said classifier training is completed.

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Bi et al., “Computer Aided Detection Via Asymmetric Cascade of Sparse Hyperplane Classifiers”, KDD '06, Aug. 20-23, 2006, Philadelphia, PA, USA, 8 pages.

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