Browsing by Subject "Signal-to-noise ratio"

Now showing 1 - 7 of 7

Open Access
Data from: Maximizing the signal-to-noise ratio of diverging ultrasonic waves in multiple scattering, attenuating, and diffracting media
(Bilkent University, 2022-09) Kumru, Yasin
Open Access
Data from: Performance of compressed sensing based image reconstruction for photoacoustic imaging
(Bilkent University, 2022-08) Çelebi, Sadık Çağatay
Open Access
Interventional MRI: tapering improves the distal sensitivity of the loopless antenna
(Wiley, 2010) Qian, D.; El-Sharkawy, A. M. M.; Atalar, Ergin; Bottomley, P. A.
The "loopless antenna" is an interventional MRI detector consisting of a tuned coaxial cable and an extended inner conductor or "whip". A limitation is the poor sensitivity afforded at, and immediately proximal to, its distal end, which is exacerbated by the extended whip length when the whip is uniformly insulated. It is shown here that tapered insulation dramatically improves the distal sensitivity of the loopless antenna by pushing the current sensitivity toward the tip. The absolute signal-to-noise ratio is numerically computed by the electromagnetic method-of-moments for three resonant 3-T antennae with no insulation, uniform insulation, and with linearly tapered insulation. The analysis shows that tapered insulation provides an ∼400% increase in signal-to-noise ratio in trans-axial planes 1 cm from the tip and a 16-fold increase in the sensitive area as compared to an equivalent, uniformly insulated antenna. These findings are directly confirmed by phantom experiments and by MRI of an aorta specimen. The results demonstrate that numerical electromagnetic signal-tonoise ratio analysis can accurately predict the loopless detector's signal-to-noise ratio and play a central role in optimizing its design. The manifold improvement in distal signal-to-noise ratio afforded by redistributing the insulation should improve the loopless antenna's utility for interventional MRI.
Open Access
Manyetik parçacık görüntüleme için sinyal-gürültü oranını eniyileyen görüntü geriçatım tekniği
(Gazi Universitesi Muhendislik-Mimarlik, 2017) Bozkurt, Ecem; Sarıtaş, Emine Ülkü
Magnetic particle imaging (MPI) is a new biomedical imaging modality that images the spatial distribution of superpamagnetic iron oxide nanoparticles. In MPI, the amplitude of the excitation magnetic field that causes the time-varying magnetization response of the nanoparticles is restricted by the nerve stimulation safety limits. Hence, the region to be imaged is divided into small sections and scanned as overlapping partial fields-of-view. The nanoparticle signal at the excitation frequency is lost during the filtering process of the direct feedthrough signal induced on the receive coil due to the excitation field. To recover this loss, the overlapping partial fields-of-view are merged via utilizing the continuity and positivity of the desired image. In this work, an image reconstruction technique that merges the partial fields-of-view while optimizing the signal-to-noise ratio is proposed. Accordingly, each partial field-of-view must be weighted by the square of the position-dependent scanning speed. Via extensive simulations at various overlap percentages and signal-to-noise ratios, this work demonstrates that the proposed method overcomes the vertical line artifacts caused by the standard MPI reconstruction techniques and improves image quality.
Open Access
Maximizing the signal-to-noise ratio of diverging ultrasonic waves in multiple scattering, attenuating, and diffracting media
(2022-09) Kumru, Yasin
Diverging wave imaging is an unfocused imaging method in which a diverging beam is transmitted to insonify the entire region of interest. This diverging beam is formed by applying appropriate time delays to each transducer array element. It provides a higher data acquisition rate and thus a higher temporal resolution, quantified as a higher frame rate. Therefore, diverging wave imaging is widely used in fast ultrasound imaging applications where rates above 1000 frames per second are required. Diverging wave imaging is generally implemented with phased array transducers having a smaller aperture than their counterparts to increase the field of view. Although diverging wave imaging allows for a high frame rate, it has a decreased spatial resolution and limited SNR due to the broader unfocused beam transmission compared to conventional focused imaging techniques. Conventional focused imaging techniques employ focused narrow beam transmissions for every image line resulting in a higher spatial resolution and SNR in the focal region. However, it offers approximately 30 frames per second, and thus it is not used in fast ultrasound imaging applications. There is a trade-off between frame rate, image quality, and SNR in diverging wave imaging. Therefore, fast imaging with high SNR and resolution while maintaining a high frame rate remains a practical problem in medical ultrasound. This thesis focuses on SNR maximization of diverging waves in weakly and multiple scattering, attenuating, and diffracting media. The primary outcome is that the SNR improves at deeper regions if the transmitted burst duration or the chip signal duration in the case of coded transmission is decreased when diverging waves are used. The maximum SNR is obtained in diverging wave transmission when the transmitted burst or the chip signal is as short-duration as the array permits. This result does not comply with the expectation implying that more transmitted energy results in higher SNR. The analytical foundation for diverging wave propagation in weakly and multiple scattering media is not sufficient at the level required to derive analytical results. In order to understand this counter-intuitive result, either finite element analysis (FEA) or semi-analytical simulation tools can be utilized. FEA can predict this counter-intuitive result, but detailed modeling of the medium is quite involved and results in very long simulation times, which renders the use of FEA impossible. Unlike the other imaging modalities, the wavelength is on the order of hundred micrometers in medical ultrasound imaging; thus, the simulation of a reasonable tissue volume is impossible. Semi-analytical simulation tools based on linear spatial impulse response produce erroneous results because scatterers are modeled as monopole sources, and multiple scattering is not modeled. As there is no analytical and simulation-based solution for this problem, the experimental verification of the results is presented. The transmitted ultrasound energy spreads over a broader region in diverging wave imaging. The energy spreading further aggravates due to diffraction and multiple scattering, which may cause energy loss. Keeping the transmitted ultrasound energy within the region of interest prevents this energy loss in diverging wave imaging. Therefore, we determined the optimum diverging wave profile to confine the transmitted ultrasound energy in the imaging sector. Using this optimized profile contributes to the SNR maximization. Complementary Golay sequences and Binary Phase Shift Keying modulation are used to code the transmitted signal. We used an ultrasound research scanner, a tissue-mimicking phantom, and a 128-element phased array transducer with 70% bandwidth at 7.5 MHz center frequency for data acquisition. The SNR in speckle and pin targets is maximized with respect to chip signal length and code length. The SNR performances of the optimized coded diverging wave and conventional single-focused phased array imaging are compared on a single frame basis. The focal region in the focused scheme is used as a reference. For the 90° imaging sector, the SNR of an 8-bit coded signal is maximum when the chip signal duration is one cycle of the center frequency. The SNR of the optimized coded diverging wave is higher than that of the conventional single-focused phased array imaging at all depths and regions. One frame of diverging wave data is acquired in 200 microseconds, equivalent to 5000 frames/s, whereas the time required for single-focused phased array imaging is 181 times more.
Open Access
Performance of compressed sensing based image reconstruction for photoacoustic imaging
(2022-08) Çelebi, Sadık Çağatay
Photoacoustic Imaging (PAI) is an emerging imaging modality that provides high resolution and image contrast. PAI employs Delay-and-Sum (DAS) beamforming in which data on all array elements are processed for image reconstruction. In order to decrease system cost in PAI, it is desired to use fewer samples in image reconstruction. Reducing the number of active elements of the array without changing the aperture decreases the computational cost. However, spatial undersampling results in poor image resolution and contrast, and causes spatial artifacts called grating lobes. Compressed Sensing (CS) is a data completion scheme that alleviates the effects of undersampling using a priori knowledge of the signal of interest and the measurement scheme. We performed simulations and experiments to compare the performances of the CS image reconstruction algorithm and conventional DAS beamforming. We used Full-Width Half Maximum (FWHM) resolution and image contrast ratio (CR) as performance metrics. Simulation results offer improved image resolution and contrast when CS is used. Lateral resolution in DAS beamformed images deteriorates with depth. A lateral resolution of 150 µm is obtained regardless of depth using only a quarter of the transducer elements. However, the resolution of DAS beamformed images ranges between 255 µm to 508 µm as the depth increases. It is also shown that CS suppresses the effects of grating lobes and improves the contrast ratio up to 14 dB. We also presented the experimental verification of the results. We used an ultrasound research scanner, a tunable laser system, and an optoacoustic phantom in the experiments. We experimentally showed that the CS method mitigates the effects of spatial undersampling and outperforms the DAS beamforming method in terms of contrast by 10.81 dB on average. CS method also offers an improved lateral resolution of approximately 350 µm compared to 750 µm in DAS beamforming.
Unknown
Statistics of the MLE and approximate upper and lower bounds-part II: Threshold computation and optimal pulse design for TOA estimation
(Institute of Electrical and Electronics Engineers Inc., 2014) Mallat, A.; Gezici, Sinan; Dardari, D.; Vandendorpe, L.
Threshold and ambiguity phenomena are studied in Part I of this paper where approximations for the mean-squared error (MSE) of the maximum-likelihood estimator are proposed using the method of interval estimation (MIE), and where approximate upper and lower bounds are derived. In this part, we consider time-of-arrival estimation and we employ the MIE to derive closed-form expressions of the begin-ambiguity, end-ambiguity and asymptotic signal-to-noise ratio (SNR) thresholds with respect to some features of the transmitted signal. Both baseband and passband pulses are considered. We prove that the begin-ambiguity threshold depends only on the shape of the envelope of the ACR, whereas the end-ambiguity and asymptotic thresholds only on the shape of the ACR. We exploit the results on the begin-ambiguity and asymptotic thresholds to optimize, with respect to the available SNR, the pulse that achieves the minimum attainable MSE. The results of this paper are valid for various estimation problems.