title: Statistical evaluation of clutter filters in color flow imaging.
abstract: The filter used to separate blood signals from the tissue clutter signal is an important part of a color flow system. In this paper, statistical detection theory is used to evaluate the quality of the most commonly used clutter filters. The probability of falsely classifying a sample volume as containing blood is kept below a specified threshold. With this constraint, the probability of correctly detecting blood is calculated for all the filters. Using a measured clutter signal, we found that polynomial regression filters and projection-initialized IIR filters are best among the commonly used filters. The probability of correctly detecting blood with velocity 10.1 cm/s was 0.32 for both these filters. The corresponding value for the optimal detector was 0.81, whereas a regression filter that depends on the clutter signal statistics achieved a blood detection probability of 0.72.
authors.affiliation: Department of Physiology and Biomedical Engineering, Norwegian University of Science and Technology, Trondheim, Norway. steinarb@medisin.ntnu.no
authors.forename: S
authors.initials: S
authors.lastname: Bjaerum
authors.forename: H
authors.initials: H
authors.lastname: Torp
mesh_terms: D001783:Blood Flow Velocity; D001808:Blood Vessels / Q000000981:diagnostic imaging*; D006801:Humans; D008962:Models, Theoretical; D013223:Statistics as Topic; D014159:Transducers; D018615:Ultrasonography, Doppler, Color / Q000295:instrumentation*