Algorithms and Results of Eye Tissues Differentiation Based on RF Ultrasound

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

Tone burst-evoked otoacoustic emissions in neonates: normative data

<p>Abstract</p> <p>Background</p> <p>Tone-burst otoacoustic emissions (TBOAEs) have not been routinely studied in pediatric populations, although tone burst stimuli have greater frequency specificity compared with click sound stimuli. The present study aimed (1) to determine an appropriate stimulus level for neonatal TBOAE measurements when the stimulus center frequency was 1 kHz, (2) to explore the characteristics of 1 kHz TBOAEs in a neonatal population.</p> <p>Methods</p> <p>A total of 395 normal neonates (745 ears) were recruited. The study consisted of two parts, reflecting the two study aims. Part I included 40 normal neonatal ears, and TBOAE measurement was performed at five stimulus levels in the range 60–80 dB peSPL, with 5 dB incremental steps. Part II investigated the characteristics of the 1 kHz TBOAE response in a large group of 705 neonatal ears, and provided clinical reference criteria based on these characteristics.</p> <p>Results</p> <p>The study provided a series of reference parameters for 1 kHz TBOAE measurement in neonates. Based on the results, a suggested stimulus level and reference criteria for 1 kHz TBOAE measures with neonates were established. In addition, time-frequency analysis of the data gave new insight into the energy distribution of the neonatal TBOAE response.</p> <p>Conclusion</p> <p>TBOAE measures may be a useful method for investigating cochlear function at specific frequency ranges in neonates. However, further studies of both TBOAE time-frequency analysis and measurements in newborns are needed.</p

О класификации эллиптических систем уравнений в частных производных второго порядка

“О класификации эллиптических систем уравнений в частных производных второго порядка”Mathematical Modelling and Analysis, 1(1), p. 36. Article in Russian. First Published Online: 14 Oct 201

The cientificWorldJOURNAL Research Article Algorithms and Results of Eye Tissues Differentiation Based on RF Ultrasound

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 timefrequency 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