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• W2142689671 abstract "First-principle approaches to the design of medical ultrasonic imaging systems for specific visual tasks are beingexplored in this paper. Our study focuses on breast cancer diagnosis and is based on the ideal observer conceptfor visual discrimination tasks, whereby tasks based on five clinical features are expressed mathematically aslikelihood functions. Realistic approximations to the ideal strategy for each task are proposed as additionalbeamforming to maximize diagnostic image information content available to readers. Our previous study showedthat a spatial Wiener filter (SWF) beamformer, derived as a stationary approximation of the ideal observerand operating on RF echo data, generally improved discriminability except for one case involving high-contrastlesions. This study explores an adaptive, iterative spatial Wiener filter (ISWF) beamformer that includes alesion segmentation algorithm to overcome the stationarity assumption and improve discriminability for highcontrastlesions. Predicted performance is compared with that measured from trained human observers usingpsychophysical methods. We found the greatest feature enhancement of the delay-and-sum beamformer followedby SWF occurs at the image formation step where RF data are converted into B-mode data. The Smith-Wagnercomputational observer, which operates on the B-mode instead of RF data, was applied to indicate performancelost by envelope detection. ISWF was found to match the performance of SWF for low-contrast lesions andincrease the performance for the high-contrast tasks. The ISWF beamforming approach offers greater diagnosticperformance for discriminating malignant and benign breast lesions, and it provides a rational basis for furthertask-specific imaging system design." @default.
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• W2142689671 date "2009-02-26" @default.
• W2142689671 modified "2023-09-26" @default.
• W2142689671 title "Ultrasonic array beamforming with iterative spatial filters" @default.
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• W2142689671 doi "https://doi.org/10.1117/12.813456" @default.
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