【摘 要】
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Background, Motivation and Objective In color flow imaging (CFI), achieving robust flow detection in the presence of tissue motion remains a long-standing challenge to be properly addressed. Key to ta
【机 构】
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Medical Engineering Program, University of Hong Kong, Pokfulam, Hong Kong
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Background, Motivation and Objective In color flow imaging (CFI), achieving robust flow detection in the presence of tissue motion remains a long-standing challenge to be properly addressed. Key to tackling this problem is the effective suppression of slow-time clutter originating from tissue echoes that contain non-zero frequency contents whenever tissue displaces during data acquisition. For some time, eigen-based clutter filtering has been tipped as an emerging solution, and it works by adaptively suppressing tissue clutter based on principal component analysis. However, the field is distinctly short of data on how much gain in flow detection sensitivity and specificity can be achieved with the use of eigen-filters.
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