A method for training classifiers for Computer-Aided Detection in medical images includes providing an image feature training set {(xi, yi)}i=1l, wherein xiεRd are 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 αk0 associated with each classifier k, fixing all classifiers except classifier k and minimizing a second cost function to solve for αkc for 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 Jc with a previous iteration Jc−1, wherein if Jc−Jc−1 is less than a predetermined tolerance, said classifier training is completed.
System and method for joint optimization of cascaded classifiers for computer aided detection