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  • C E Metz
  • 1978
The limitations of diagnostic "accuracy" as a measure of decision performance require introduction of the concepts of the "sensitivity" and "specificity" of a diagnostic test. These measures and the related indices, "true positive fraction" and "false positive fraction," are more meaningful than "accuracy," yet do not provide a unique description of(More)
The authors investigated the potential utility of artificial neural networks as a decision-making aid to radiologists in the analysis of mammographic data. Three-layer, feed-forward neural networks with a back-propagation algorithm were trained for the interpretation of mammograms on the basis of features extracted from mammograms by experienced(More)
Receiver operating characteristic (ROC) analysis provides the most comprehensive description of diagnostic accuracy available to date, because it estimates and reports all of the combinations of sensitivity and specificity that a diagnostic test is able to provide. After sketching the 6 levels at which diagnostic efficacy can be assessed, this paper(More)
In conventional receiver-operating-characteristic (ROC) curve analysis of visual detection performance, the observer is credited with a true-positive response if a visual signal is present somewhere in a radiograph called "positive" by the observer; however, the measured true-positive rate can be different for a given false-positive rate if the observer is(More)
We express the performance of the N-class "guessing" observer in terms of the N2-N conditional probabilities which make up an N-class receiver operating characteristic (ROC) space, in a formulation in which sensitivities are eliminated in constructing the ROC space (equivalent to using false-negative fraction and false-positive fraction in a two-class(More)
Classifier design for a given classification task needs to take into consideration both the complexity of the classifier and the size of the dataset that is available for training the classifier. With limited training data, as often is the situation in computer-aided diagnosis of medical images, a classifier with simple structure (e.g., a linear classifier)(More)
PURPOSE To determine the effect of computer-aided diagnosis (CAD) on the accuracy of pulmonary nodule detection. MATERIALS AND METHODS Twenty abnormal chest radiographs, each with a single nodule, and 20 normal radiographs were digitized with a laser scanner. These images were analyzed by using a computer program that indicates areas that may represent(More)
Detection studies of simulated low-contrast radiographic patterns were performed with a high-quality digital image processing system. The original images, prepared with conventional screen-film systems, were processed digitally to enhance contrast by a "windowing" technique. The detectability of simulated patterns was quantified in terms of the results of(More)
Exact methods of inverting the two-dimensional (2-D) exponential Radon transform have been proposed by Bellini et al. (1979) and by Inouye et al. (1989), both of whom worked in the spatial-frequency domain to estimate the 2-D Fourier transform of the unattenuated sinogram; by Hawkins et al. (1988), who worked with circularly harmonic Bessel transforms; and(More)
A general approach that the authors proposed elsewhere reveals the intrinsic relationship among methods for inversion of the 2-D exponential Radon transform described by Bellini et al. (1979), by Tretiak and Metz (1980), by Hawkins et al. (1988), and by Inouye et al. (1989). Moreover, the authors' approach provides an infinite class of linear methods for(More)