Analysis of Doppler ultrasound signals based on fuzzy similarity index

Abstract

Abstract In this paper, we introduced fuzzy similarity index for analysis of the Doppler ultrasound signals. Doppler ultrasonography is a reliable technique, which demonstrates the flow characteristics and resistance of arteries in various arterial diseases. The analyzed ophthalmic arterial (OA) Doppler signals were recorded from healthy subjects and subjects suffering from ophthalmic artery stenosis, ocular Behcet disease and uveitis disease. The OA Doppler signals were decomposed into time–frequency representations using discrete wavelet transform and wavelet coefficients were calculated to represent the signals. The aim of the study is discriminating the OA Doppler signals by the combination of wavelet coefficients and fuzzy similarity index. Toward achieving this aim, fuzzy sets were obtained from the feature sets (wavelet coefficients) of the signals under study. Our results demonstrated that the similarity between the fuzzy sets of the studied signals indicated the variabilities in the OA Doppler signals. Thus, the fuzzy similarity index could discriminate the healthy OA Doppler signals and the other three disease states (stenosis, ocular Behcet disease and uveitis).