Simultaneous multi-slice echo planar diffusion weighted imaging of the liver and the pancreas: Optimization of signal-to-noise ratio and acquisition time and application to intravoxel incoherent motion analysis

2016 ◽  
Vol 85 (11) ◽  
pp. 1948-1955 ◽  
Author(s):  
Andreas Boss ◽  
Borna Barth ◽  
Lukas Filli ◽  
David Kenkel ◽  
Moritz C. Wurnig ◽  
...  
Keyword(s):  
Motion Analysis ◽  
Diffusion Weighted Imaging ◽  
Signal To Noise Ratio ◽  
Intravoxel Incoherent Motion ◽  
Acquisition Time ◽  
Signal To Noise ◽  
Diffusion Weighted ◽  
Noise Ratio ◽  
Echo Planar

Signal-to-Noise Ratio importance in Apparent Diffusion Coefficient measurements using Diffusion-Weighted Echo-Planar-Imaging scans

2014 ◽  
Vol 4 (2) ◽  
pp. 517-525
Author(s):  
Cristiano Biagini ◽  
Martina De Michele ◽  
Andrea Pratesi ◽  
Francesco Mungai ◽  
Margherita Betti ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Signal To Noise Ratio ◽  
Planar Imaging ◽  
Signal To Noise ◽  
Diffusion Weighted ◽  
Apparent Diffusion ◽  
Noise Ratio ◽  
Echo Planar

Purpose: To define experimental grounds for Apparent Diffusion Coefficient (ADC) measurements using Spin-Echo Diffusion-Weighted Echo-Planar (SE-DW-EPI) sequences, as a function of Signal-to-Noise Ratio (SNR).Methods: multiple multi-b SE-DW-EPI scans with the same parameters but the lipid suppression technique have been compared on water phantom with a 3T MRI equipment. The SNR has been estimated using the method of difference. Images have been analyzed manually, comparing the signal intensities at different b-values.Results: All measurements show a high repeatability and strong self-consistency. A significant dependence of the ADC on SNR has been shown, and its lowest limitto obtain reliable quantitative answers has been stated.Conclusion: ADC measurements in vivo must be carefully designed to avoid systematic errors during acquisition and post-processing due to low SNR.

Information capacity and bandwidth limitations in the SEM

1989 ◽  
Vol 47 ◽  
pp. 84-85
Author(s):  
D. C. Joy ◽  
R. D. Bunn
Keyword(s):  
Signal To Noise Ratio ◽  
Critical Dimension ◽  
Information Capacity ◽  
Acquisition Time ◽  
Signal To Noise ◽  
Sem Image ◽  
Probe Size ◽  
Minimum Number ◽  
Noise Ratio ◽  
Signal Channel

The information available from an SEM image is limited both by the inherent signal to noise ratio that characterizes the image and as a result of the transformations that it may undergo as it is passed through the amplifying circuits of the instrument. In applications such as Critical Dimension Metrology it is necessary to be able to quantify these limitations in order to be able to assess the likely precision of any measurement made with the microscope.The information capacity of an SEM signal, defined as the minimum number of bits needed to encode the output signal, depends on the signal to noise ratio of the image - which in turn depends on the probe size and source brightness and acquisition time per pixel - and on the efficiency of the specimen in producing the signal that is being observed. A detailed analysis of the secondary electron case shows that the information capacity C (bits/pixel) of the SEM signal channel could be written as :

Image Acquisition Using Non-Pixeled Amorphous Silicon Based Sensors

2001 ◽  
Vol 685 ◽  
Author(s):  
M. Fernandes ◽  
Yu. Vygranenko ◽  
J. Martins ◽  
M. Vieira
Keyword(s):  
Amorphous Silicon ◽  
Signal To Noise Ratio ◽  
Image Acquisition ◽  
Short Circuit ◽  
Acquisition Time ◽  
Large Area ◽  
Signal To Noise ◽  
Scanning Beam ◽  
Noise Ratio ◽  
Silicon Based

AbstractWe suggest to enhance the performance of image acquisition systems based on large area amorphous silicon based sensors by optimizing the readout parameters such as the intensity and cross-section of scanner beam, acquisition time and bias conditions. The main output device characteristics as image responsivity, signal to noise ratio and spatial resolution were analyzed in open circuit, short circuit and photodiode modes. The result show that the highest signal to noise ratio and best dark to bright ratio can be achieved in short circuit mode.It was shown that the sensor resolution is related to the basic device parameters and, in practice, limited by the acquisition time and scanning beam properties. The scanning beam spot size limits the resolution due to the overlapping of dark and illuminated zones leading to a blurring effect on the final image and a consequent degradation in the resolution.

Clinical impact of ultra-high b-value (3000 s/mm2) diffusion-weighted magnetic resonance imaging in prostate cancer at 3T: comparison with b-value of 2000 s/mm2

2021 ◽  
pp. 20210465
Author(s):  
Tsutomu Tamada ◽  
Ayumu Kido ◽  
Yu Ueda ◽  
Mitsuru Takeuchi ◽  
Takeshi Fukunaga ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Diagnostic Performance ◽  
Signal To Noise Ratio ◽  
B Value ◽  
Single Shot ◽  
Signal To Noise ◽  
High B Value ◽  
Diffusion Weighted ◽  
Significant Difference ◽  
Noise Ratio

Objective: High b-value diffusion-weighted imaging (hDWI) with a b-value of 2000 s/mm2 provides insufficient image contrast between benign and malignant tissues and an overlap of apparent diffusion coefficient (ADC) between Gleason grades (GG) in prostate cancer (PC). We compared image quality, PC detectability, and discrimination ability for PC aggressiveness between ultra-high b-value DWI (uhDWI) of 3000 s/mm2 and hDWI. Methods: The subjects were 49 patients with PC who underwent 3T multiparametric MRI. Single-shot echo-planar DWI was acquired with b-values of 0, 2000, and 3000 s/mm2. Anatomical distortion of prostate (AD), signal intensity of benign prostate (PSI), and lesion conspicuity score (LCS) were assessed using a 4-point scale; and signal-to-noise ratio, contrast-to-noise ratio, and mean ADC (×10–3 mm2/s) of lesion (lADC) and surrounding benign region (bADC) were measured. Results: PSI was significantly lower in uhDWI than in hDWI (p < 0.001). AD, LCS, signal-to-noise ratio, and contrast-to-noise ratio were comparable between uhDWI and hDWI (all p > 0.05). In contrast, lADC was significantly lower than bADC in both uhDWI and hDWI (both p < 0.001). In comparison of lADC between tumors of ≤GG2 and those of ≥GG3, both uhDWI and hDWI showed significant difference (p = 0.007 and p = 0.021, respectively). AUC for separating tumors of ≤GG2 from those of ≥GG3 was 0.731 in hDWI and 0.699 in uhDWI (p = 0.161). Conclusion: uhDWI suppressed background signal better than hDWI, but did not contribute to increased diagnostic performance in PC. Advances in knowledge: Compared with hDWI, uhDWI could not contribute to increased diagnostic performance in PC.

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