Tissue Flow Detection Using Fuzzy Logic Method in Color Flow Imaging

Xiaoming Zhou, Wen Liu

Abstract


Tissue/flow detection is critical for high quality 2-D color flow image. The traditional tissue/flow detection method is based on one or several thresholds which are used for parameters after autocorrelation. Generally a lot of parameters: flow magnitude, variance and velocity are applied for tissue/flow detection. But this method may not distinguish tissue/flow because of moving tissue or noise. So in this paper, fuzzy logic method with multi-level range based on in vivo carotid I/Q data was proposed with three parameters: echo amplitude, flow magnitude and Flow variance for tissue/flow detection and then decision look-up-table (LUT) was designed for real time display. Experiment results shows that fuzzy logic method was improved for tissue flow detection significantly and can get high quality 2-D color flow image.

Keywords


tissue/flow detection; echo amplitude; flow magnitude; Flow variance; fuzzy logic;

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DOI: http://doi.org/10.11591/ijeecs.v12.i9.pp6840-6845

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The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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