19 resultados para low noise amplifier (LNA)
Resumo:
Road-traffic noise impairs the well-being and health of many people. Motivating car drivers to voluntarily adopt a low-noise driving style (i.e., eco-driving) contributes to the reduction of road-traffic noise, complementary to requirements, bans, and laws. In a field study with employees of a municipality (N = 88), we investigated the effects of an intervention on car drivers’ motivation to prevent road-traffic noise, motivation to practice eco-driving, and driving behavior. The intervention consisted of a leaflet intended to enhance participants’ motivation, a practical eco-driving course, and weekly driving-performance feedbacks. We used a switching-replications design with two intervention groups. In both groups, eco-driving behavior was significantly strengthened by the intervention. The effects on the motivational variables were significant in only one of the groups (however, it should be noted that the average motivation was already relatively high before the intervention). For one of the groups, the study design allowed testing for the effects at an additional follow-up assessment (4 months after the intervention). The results showed that the intervention effect on driving behavior held across this period. The findings of the present research suggest that it is possible to improve car driver’s behavior with regard to a low-noise driving style.
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This paper introduces an area- and power-efficient approach for compressive recording of cortical signals used in an implantable system prior to transmission. Recent research on compressive sensing has shown promising results for sub-Nyquist sampling of sparse biological signals. Still, any large-scale implementation of this technique faces critical issues caused by the increased hardware intensity. The cost of implementing compressive sensing in a multichannel system in terms of area usage can be significantly higher than a conventional data acquisition system without compression. To tackle this issue, a new multichannel compressive sensing scheme which exploits the spatial sparsity of the signals recorded from the electrodes of the sensor array is proposed. The analysis shows that using this method, the power efficiency is preserved to a great extent while the area overhead is significantly reduced resulting in an improved power-area product. The proposed circuit architecture is implemented in a UMC 0.18 [Formula: see text]m CMOS technology. Extensive performance analysis and design optimization has been done resulting in a low-noise, compact and power-efficient implementation. The results of simulations and subsequent reconstructions show the possibility of recovering fourfold compressed intracranial EEG signals with an SNR as high as 21.8 dB, while consuming 10.5 [Formula: see text]W of power within an effective area of 250 [Formula: see text]m × 250 [Formula: see text]m per channel.
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Imaging of biological samples has been performed with a variety of techniques for example electromagnetic waves, electrons, neutrons, ultrasound and X-rays. Also conventional X-ray imaging represents the basis of medical diagnostic imaging, it remains of limited use in this application because it is based solely on the differential absorption of X-rays by tissues. Coherent and bright photon beams, such as those produced by third-generation synchrotron X-ray sources, provide further information on subtle X-ray phase changes at matter interfaces. This complements conventional X-ray absorption by edge enhancement phenomena. Thus, phase contrast imaging has the potential to improve the detection of structures on images by detecting those structures that are invisible with X-ray absorption imaging. Images of a weakly absorbing nylon fibre were recorded in in-line holography geometry using a high resolution low-noise CCD camera at the ESRF in Grenoble. The method was also applied to improve image contrast for images of biological tissues. This paper presents phase contrast microradiographs of vascular tree casts and images of a housefly. These reveal very fine structures, that remain invisible with conventional absorption contrast only.
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The CHaracterising ExOPlanet Satellite (CHEOPS) is a joint ESA-Switzerland space mission (expected to launch in 2017) dedicated to search for exoplanet transits by means of ultra-high precision photometry. CHEOPS will provide accurate radii for planets down to Earth size. Targets will mainly come from radial velocity surveys. The CHEOPS instrument is an optical space telescope of 30 cm clear aperture with a single focal plane CCD detector. The tube assembly is passively cooled and thermally controlled to support high precision, low noise photometry. The telescope feeds a re-imaging optic, which supports the straylight suppression concept to achieve the required Signal to Noise. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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To study the effect of a nonlinear noise filter on the detection of simulated endoleaks in a phantom with 80- and 100-kVp multidetector computed tomographic (CT) angiography.
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We demonstrated all-fiber amplification of 11 ps pulses from a gain-switched laser diode at 1064 nm. The diode was driven at a repetition rate of 40 MHz and delivered 13 µW of fiber-coupled average output power. For the low output pulse energy of 325 fJ we have designed a multi-stage core pumped pre-amplifier in order to keep the contribution of undesired amplified spontaneous emission as low as possible. By using a novel time-domain approach for determining the power spectral density ratio (PSD) of signal to noise, we identified the optimal working point for our pre-amplifier. After the pre-amplifier we reduced the 40 MHz repetition rate to 1 MHz using a fiber coupled pulse-picker. The final amplification was done with a cladding pumped Yb-doped large mode area fiber and a subsequent Yb-doped rod-type fiber. With our setup we reached a total gain of 73 dB, resulting in pulse energies of >5.6 µJ and peak powers of >0.5 MW. The average PSD-ratio of signal to noise we determined to be 18/1 at the output of the final amplification stage.
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Low-field (LF) (0.2-0.4T) magnetic resonance (MR) imaging predominates in veterinary practice. Advantages of LF MR include reduced costs, better patient access, and greater safety. High quality examinations can be achieved using appropriate protocols and investing more scanning time than with high-field (HF) systems. The main disadvantage of LF MR is the reduced signal to noise ratio compared with HF systems. LF MR protocols for small animal brain and spine imaging are described.
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A new generation of high definition computed tomography (HDCT) 64-slice devices complemented by a new iterative image reconstruction algorithm-adaptive statistical iterative reconstruction, offer substantially higher resolution compared to standard definition CT (SDCT) scanners. As high resolution confers higher noise we have compared image quality and radiation dose of coronary computed tomography angiography (CCTA) from HDCT versus SDCT. Consecutive patients (n = 93) underwent HDCT, and were compared to 93 patients who had previously undergone CCTA with SDCT matched for heart rate (HR), HR variability and body mass index (BMI). Tube voltage and current were adapted to the patient's BMI, using identical protocols in both groups. The image quality of all CCTA scans was evaluated by two independent readers in all coronary segments using a 4-point scale (1, excellent image quality; 2, blurring of the vessel wall; 3, image with artefacts but evaluative; 4, non-evaluative). Effective radiation dose was calculated from DLP multiplied by a conversion factor (0.014 mSv/mGy × cm). The mean image quality score from HDCT versus SDCT was comparable (2.02 ± 0.68 vs. 2.00 ± 0.76). Mean effective radiation dose did not significantly differ between HDCT (1.7 ± 0.6 mSv, range 1.0-3.7 mSv) and SDCT (1.9 ± 0.8 mSv, range 0.8-5.5 mSv; P = n.s.). HDCT scanners allow low-dose 64-slice CCTA scanning with higher resolution than SDCT but maintained image quality and equally low radiation dose. Whether this will translate into higher accuracy of HDCT for CAD detection remains to be evaluated.
Resumo:
PURPOSE: To prospectively evaluate, for the depiction of simulated hypervascular liver lesions in a phantom, the effect of a low tube voltage, high tube current computed tomographic (CT) technique on image noise, contrast-to-noise ratio (CNR), lesion conspicuity, and radiation dose. MATERIALS AND METHODS: A custom liver phantom containing 16 cylindric cavities (four cavities each of 3, 5, 8, and 15 mm in diameter) filled with various iodinated solutions to simulate hypervascular liver lesions was scanned with a 64-section multi-detector row CT scanner at 140, 120, 100, and 80 kVp, with corresponding tube current-time product settings at 225, 275, 420, and 675 mAs, respectively. The CNRs for six simulated lesions filled with different iodinated solutions were calculated. A figure of merit (FOM) for each lesion was computed as the ratio of CNR2 to effective dose (ED). Three radiologists independently graded the conspicuity of 16 simulated lesions. An anthropomorphic phantom was scanned to evaluate the ED. Statistical analysis included one-way analysis of variance. RESULTS: Image noise increased by 45% with the 80-kVp protocol compared with the 140-kVp protocol (P < .001). However, the lowest ED and the highest CNR were achieved with the 80-kVp protocol. The FOM results indicated that at a constant ED, a reduction of tube voltage from 140 to 120, 100, and 80 kVp increased the CNR by factors of at least 1.6, 2.4, and 3.6, respectively (P < .001). At a constant CNR, corresponding reductions in ED were by a factor of 2.5, 5.5, and 12.7, respectively (P < .001). The highest lesion conspicuity was achieved with the 80-kVp protocol. CONCLUSION: The CNR of simulated hypervascular liver lesions can be substantially increased and the radiation dose reduced by using an 80-kVp, high tube current CT technique.
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OBJECTIVE: Measures to reduce radiation exposure and injected iodine mass are becoming more important with the widespread and often repetitive use of pulmonary CT angiography (CTA) in patients with suspected pulmonary embolism. In this retrospective study, we analyzed the capability of 2 low-kilovoltage CTA-protocols to achieve these goals. MATERIALS AND METHODS: Ninety patients weighing less than 100 kg were examined by a pulmonary CTA protocol using either 100 kVp (group A) or 80 kVp (group B). Volume and flow rate of contrast medium were reduced in group B (75 mL at 3 mL/s) compared with group A (100 mL at 4 mL/s). Attenuation was measured in the central and peripheral pulmonary arteries, and the contrast-to-noise ratios (CNR) were calculated. Entrance skin dose was estimated by measuring the surface dose in an ovoid-cylindrical polymethyl methacrylate chest phantom with 2 various dimensions corresponding to the range of chest diameters in our patients. Quantitative image parameters, estimated effective dose, and skin dose in both groups were compared by the t test. Arterial enhancement, noise, and overall quality were independently assessed by 3 radiologists, and results were compared between the groups using nonparametric tests. RESULTS: Mean attenuation in the pulmonary arteries in group B (427.6 +/- 116 HU) was significantly higher than in group A (342.1 +/- 87.7 HU; P < 0.001), whereas CNR showed no difference (group A, 20.6 +/- 7.3 and group B, 22.2 +/- 7.1; P = 0.302). Effective dose was lower by more than 40% with 80 kVp (1.68 +/- 0.23 mSv) compared with 100 kVp (2.87 +/- 0.88 mSv) (P < 0.001). Surface dose was significantly lower at 80 kVp compared with 100 kVp at both phantom dimensions (2.75 vs. 3.22 mGy; P = 0.027 and 2.22 vs. 2.73 mGy; P = 0.005, respectively). Image quality did not differ significantly between the groups (P = 0.151). CONCLUSIONS: Using 80 kVp in pulmonary CTA permits reduced patient exposure by 40% and CM volume by 25% compared with 100 kVp without deterioration of image quality in patients weighing less than 100 kg.
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The objective of this retrospective study was to assess image quality with pulmonary CT angiography (CTA) using 80 kVp and to find anthropomorphic parameters other than body weight (BW) to serve as selection criteria for low-dose CTA. Attenuation in the pulmonary arteries, anteroposterior and lateral diameters, cross-sectional area and soft-tissue thickness of the chest were measured in 100 consecutive patients weighing less than 100 kg with 80 kVp pulmonary CTA. Body surface area (BSA) and contrast-to-noise ratios (CNR) were calculated. Three radiologists analyzed arterial enhancement, noise, and image quality. Image parameters between patients grouped by BW (group 1: 0-50 kg; groups 2-6: 51-100 kg, decadally increasing) were compared. CNR was higher in patients weighing less than 60 kg than in the BW groups 71-99 kg (P between 0.025 and <0.001). Subjective ranking of enhancement (P = 0.165-0.605), noise (P = 0.063), and image quality (P = 0.079) did not differ significantly across all patient groups. CNR correlated moderately strongly with weight (R = -0.585), BSA (R = -0.582), cross-sectional area (R = -0.544), and anteroposterior diameter of the chest (R = -0.457; P < 0.001 all parameters). We conclude that 80 kVp pulmonary CTA permits diagnostic image quality in patients weighing up to 100 kg. Body weight is a suitable criterion to select patients for low-dose pulmonary CTA.
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RATIONALE AND OBJECTIVES: To evaluate the effect of automatic tube current modulation on radiation dose and image quality for low tube voltage computed tomography (CT) angiography. MATERIALS AND METHODS: An anthropomorphic phantom was scanned with a 64-section CT scanner using following tube voltages: 140 kVp (Protocol A), 120 kVp (Protocol B), 100 kVp (Protocol C), and 80 kVp (Protocol D). To achieve similar noise, combined z-axis and xy-axes automatic tube current modulation was applied. Effective dose (ED) for the four tube voltages was assessed. Three plastic vials filled with different concentrations of iodinated solution were placed on the phantom's abdomen to obtain attenuation measurements. The signal-to-noise ratio (SNR) was calculated and a figure of merit (FOM) for each iodinated solution was computed as SNR(2)/ED. RESULTS: The ED was kept similar for the four different tube voltages: (A) 5.4 mSv +/- 0.3, (B) 4.1 mSv +/- 0.6, (C) 3.9 mSv +/- 0.5, and (D) 4.2 mSv +/- 0.3 (P > .05). As the tube voltage decreased from 140 to 80 kVp, image noise was maintained (range, 13.8-14.9 HU) (P > .05). SNR increased as the tube voltage decreased, with an overall gain of 119% for the 80-kVp compared to the 140-kVp protocol (P < .05). The FOM results indicated that with a reduction of the tube voltage from 140 to 120, 100, and 80 kVp, at constant SNR, ED was reduced by a factor of 2.1, 3.3, and 5.1, respectively, (P < .001). CONCLUSIONS: As tube voltage decreases, automatic tube current modulation for CT angiography yields either a significant increase in image quality at constant radiation dose or a significant decrease in radiation dose at a constant image quality.
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We consider the problem of fitting a union of subspaces to a collection of data points drawn from one or more subspaces and corrupted by noise and/or gross errors. We pose this problem as a non-convex optimization problem, where the goal is to decompose the corrupted data matrix as the sum of a clean and self-expressive dictionary plus a matrix of noise and/or gross errors. By self-expressive we mean a dictionary whose atoms can be expressed as linear combinations of themselves with low-rank coefficients. In the case of noisy data, our key contribution is to show that this non-convex matrix decomposition problem can be solved in closed form from the SVD of the noisy data matrix. The solution involves a novel polynomial thresholding operator on the singular values of the data matrix, which requires minimal shrinkage. For one subspace, a particular case of our framework leads to classical PCA, which requires no shrinkage. For multiple subspaces, the low-rank coefficients obtained by our framework can be used to construct a data affinity matrix from which the clustering of the data according to the subspaces can be obtained by spectral clustering. In the case of data corrupted by gross errors, we solve the problem using an alternating minimization approach, which combines our polynomial thresholding operator with the more traditional shrinkage-thresholding operator. Experiments on motion segmentation and face clustering show that our framework performs on par with state-of-the-art techniques at a reduced computational cost.