Algorithms and Results of Eye Tissues Differentiation Based on RF Ultrasound

Abstract

Algorithms and software were developed for analysis of B-scan ultrasonic signals acquired from commercial diagnostic ultrasound system. The algorithms process raw ultrasonic signals in backscattered spectrum domain, which is obtained using two time-frequency methods: short-time Fourier and Hilbert-Huang transformations. The signals from selected regions of eye tissues are characterized by parameters: B-scan envelope amplitude, approximated spectral slope, approximated spectral intercept, mean instantaneous frequency, mean instantaneous bandwidth, and parameters of Nakagami distribution characterizing Hilbert-Huang transformation output. The backscattered ultrasound signal parameters characterizing intraocular and orbit tissues were processed by decision tree data mining algorithm. The pilot trial proved that applied methods are able to correctly classify signals from corpus vitreum blood, extraocular muscle, and orbit tissues. In 26 cases of ocular tissues classification, one error occurred, when tissues were classified into classes of corpus vitreum blood, extraocular muscle, and orbit tissue. In this pilot classification parameters of spectral intercept and Nakagami parameter for instantaneous frequencies distribution of the 1st intrinsic mode function were found specific for corpus vitreum blood, orbit and extraocular muscle tissues. We conclude that ultrasound data should be further collected in clinical database to establish background for decision support system for ocular tissue noninvasive differentiation.

Electromagnetic limits to radiofrequency (RF) neuronal telemetry

“…Implicit in the implanted sensor application is the requirement for the telemetry stream to negotiate the propagation properties of living tissue. A variety of modalities have been explored for transmitting energy and information through biological media, including: magnetic fields (MRI 4 and near-field powered devices 5 ), microwave 6 , ultrasound 7 8 , Infrared 9 and photonic 10 . The exacting requirements of magnetic field strength and uniformity for micro-MRI are well documented, and in general limit the method to the examination of small biological volumes that can be contained within the controlled field environment.…”

Characterization of benign thyroid nodules with HyperSPACE (Hyper Spectral Analysis for Characterization in Echography) before and after percutaneous laser ablation: a pilot study

“…In addition, US can be used to obtain information on the composition of the nodular tissue by using spectral analysis of the radiofrequency signal (RF) which contains information about ultrasound-tissue interactions [16][17][18][19]. Through the identification of new coefficients [20][21][22][23][24][25][26], the spectral analysis of the RF signal is able to provide information regarding the biological structure of the tissue.…”