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Ideal Observer Approximation Using Bayesian Classification Neural Networks.

, , , and . IEEE Trans. Med. Imaging, 20 (9): 886-899 (2001)

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Computerized detection and 3-way classification of breast lesions on ultrasound images., , , , and . Medical Imaging: Image Processing, volume 5370 of SPIE Proceedings, SPIE, (2004)Eliminating false-positive microcalcification clusters in a mammography CAD scheme using a Bayesian neural network., , , , and . Medical Imaging: Image Processing, volume 4322 of SPIE Proceedings, SPIE, (2001)Restrictions on the three-class ideal observer's decision boundary lines., and . IEEE Trans. Med. Imaging, 24 (12): 1566-1573 (2005)Ideal Observer Approximation Using Bayesian Classification Neural Networks., , , and . IEEE Trans. Med. Imaging, 20 (9): 886-899 (2001)Ideal observers and optimal ROC hypersurfaces in N-class classification., , and . IEEE Trans. Med. Imaging, 23 (7): 891-895 (2004)Comparison of two-class and three-class Bayesian artificial neural networks in estimation of observations drawn from simulated bivariate normal distributions., , and . Medical Imaging: Computer-Aided Diagnosis, volume 7963 of SPIE Proceedings, page 796325. SPIE, (2011)Using three-class BANN classifier in the automated analysis of breast cancer lesions in DCE-MRI., , , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 7260 of SPIE Proceedings, page 72600J. SPIE, (2009)The hypervolume under the ROC hypersurface of "Near-Guessing" and Near-Perfect" observers in N-class classification tasks., , and . IEEE Trans. Med. Imaging, 24 (3): 293-299 (2005)Optimization of Restricted ROC Surfaces in Three-Class Classification Tasks., and . IEEE Trans. Med. Imaging, 26 (10): 1345-1356 (2007)