Image processing and image reconstruction with the use of a-priori information. - Chin-Tu Chen; Valen E. Johnson; Xiaoping Hu 001; Wing H. Wong; Charles E. Metz (Image Processing, 1990)

Investigation of methods for the computerized detection and analysis of mammographic masses. - Maryellen Lissak Giger; Fang-Fang Yin; Kunio Doi; Charles E. Metz; Robert A. Schmidt; Carl J. Vyborny (Image Processing, 1990)

Simulation studies of data classification by artificial neural networks: Potential applications in medical imaging and decision making. - Yuzheng C. Wu; Kunio Doi; Charles E. Metz; Naoki Asada; Maryellen L. Giger (J. Digit. Imaging, 1993)

Reduction of false positives in computerized detection of lung nodules in chest radiographs using artificial neural networks, discriminant analysis, and a rule-based scheme. - Yuzheng C. Wu; Kunio Doi; Maryellen L. Giger; Charles E. Metz; Wei Zhang (J. Digit. Imaging, 1994)

A unified analysis of exact methods of inverting the 2-D exponential radon transform, with implications for noise control in SPECT. - Charles E. Metz; Xiaochuan Pan (IEEE Trans. Medical Imaging, 1995)

Analysis of noise properties of a class of exact methods of inverting the 2-D exponential radon transform [SPECT application]. - Xiaochuan Pan; Charles E. Metz (IEEE Trans. Medical Imaging, 1995)

Benefits of Computer-Aided Diagnosis (CAD) in Mammographic Diagnosis of Malignant and Benign Clustered Microcalcifications. - Yulei Jiang; Robert M. Nishikawa; Robert A. Schmidt; Charles E. Metz; Maryellen L. Giger; Kunio Doi (Digital Mammography / IWDM, 1998)

Ideal Observer Approximation Using Bayesian Classification Neural Networks. - Matthew A. Kupinski; Darrin C. Edwards; Maryellen L. Giger; Charles E. Metz (IEEE Trans. Medical Imaging, 2001)

Comparison of two methods of adding jitter to artificial neural network training. - R. M. Zur; Y. Jiang; Charles E. Metz (CARS, 2004)

Computerized detection and 3-way classification of breast lesions on ultrasound images. - Karen Drukker; Darrin C. Edwards; Maryellen Lissak Giger; Robert M. Nishikawa; Charles E. Metz (Image Processing, 2004)

Ideal observers and optimal ROC hypersurfaces in N-class classification. - Darrin C. Edwards; Charles E. Metz; Matthew A. Kupinski (IEEE Trans. Medical Imaging, 2004)

Restrictions on the three-class ideal observer's decision boundary lines. - Darrin C. Edwards; Charles E. Metz (IEEE Trans. Medical Imaging, 2005)

The hypervolume under the ROC hypersurface of "Near-Guessing" and Near-Perfect" observers in N-class classification tasks. - Darrin C. Edwards; Charles E. Metz; Robert M. Nishikawa (IEEE Trans. Medical Imaging, 2005)

Three-class ROC analysis-a decision theoretic approach under the ideal observer framework. - Xin He; Charles E. Metz; Benjamin M. W. Tsui; Jonathan M. Links; Eric C. Frey (IEEE Trans. Medical Imaging, 2006)

Optimization of Restricted ROC Surfaces in Three-Class Classification Tasks. - Darrin C. Edwards; Charles E. Metz (IEEE Trans. Medical Imaging, 2007)

Hybrid linear classifier for jointly normal data: theory. - Weijie Chen 007; Charles E. Metz; Maryellen L. Giger (Computer-Aided Diagnosis, 2008)

A Novel Hybrid Linear/Nonlinear Classifier for Two-Class Classification: Theory, Algorithm, and Applications. - Weijie Chen 007; Charles E. Metz; Maryellen L. Giger; Karen Drukker (IEEE Trans. Medical Imaging, 2010)