Evaluating the efficient of imaging processes

Shaw, Rodney

doi:10.1088/0034-4885/41/7/003

Cited by 46 publications

(23 citation statements)

References 184 publications

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“…In the small signal limit the logarithmic measure is simply proportional to the SNR 2 in the channel (Shaw 1963, here written as We see that the NEQ(f) approach and the Shannon channel approach lead to the same measure (Shaw 1963). (Shaw (1978) points out that Shannon's approach to the quantification of information in noisy communications channels is actually more general than the thermodynamics it resembles since it is applicable to problems involving any kind of uncertainty.) The ideal observer SNR 2 is just an integral over the NEQ(f) spectrumdetermined by the system detection hardware-weighted by the spectrum of a difference signal-corresponding to the observer's task (equation 10):…”

Section: The Snr(f) Spectrum and The Concept Of The Aperturementioning

confidence: 89%

Unified SNR analysis of medical imaging systems

1985

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The ideal observer signal to noise ratio (SNR) has been derived from statistical decision theory for all of the major medical imaging modalities. This SNR provides an absolute scale for image system performance assessment and leads to instrumentation design goals and constraints for imaging system optimisation since no observer can surpass the performance of the ideal observer. The dependence of detectable detail size on exposure or imaging time follows immediately from the analysis. A framework emerges for comparing data acquisition techniques, e.g. reconstruction from projections versus Fourier methods in NMR imaging, and time of flight positron emission tomography (TOFPET) versus conventional PET. The approach of studying the ideal observer is motivated by measurements on human observers which show that they can come close to the performance of the idea) observer, except when the image noise has negative correlations-as in images reconstructed from projections-where they suffer a small but significant penalty.

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Section: The Snr(f) Spectrum and The Concept Of The Aperturementioning

confidence: 89%

Unified SNR analysis of medical imaging systems

1985

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Section: Noise Equivalent Quanta (Neq) and Dqementioning

confidence: 99%

“…This quantity, known as the Noise Equivalent Quanta, is expressed in (8) [17]. (8) The definition of NEQ and (6) allow representing the Detective Quantum Efficiency in the form of (9) [17]. (9) Thus, DQE is a ratio that describes the efficiency of the system in utilizing the incident neutrons to produce an output with a desired SNR.…”

Section: Noise Equivalent Quanta (Neq) and Dqementioning

confidence: 99%

Noise evaluation of a digital neutron imaging device

Lewandowski¹,

Cao²,

Turkoglu³

2012

Nuclear Instruments and Methods in Physics Research Section A:

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Radiography consists of methods aimed at providing a nondestructive mean of imaging internal structures and composition of matter by recording the transmitted intensity of a beam of radiation. The enormous popularity of X-ray imaging in medicine has driven an effort in X-ray radiography aimed at standardizing and regulating the acquisition of X-ray radiographs and quantifying image quality across different X-ray platforms. However, a similar discussion has not been observed in neutron radiography (NR), a type of imaging technique that uses neutrons as a source of radiation. Currently, the Modulation Transfer Function (MTF) is solely used to measure the quality of NR systems. However, MTF is a measure of contrast only and does not account for noise.The purpose of this research was to take additional metrics including the Noise Power Spectrum (NPS) and the Detective Quantum Efficiency (DQE) that are commonly used in X-ray imaging, apply them to NR, and evaluate the impact of noise. An imaging system was developed using a low-cost digital camera, modified with open source software to enhance imaging capabilities. The system allowed capturing images of a neutron beam produced by the OSU Research Reactor at various exposure times. The produced images were analyzed with the help of MATLAB to establish MTF, NPS, and DQE measurements. The results confirmed the initial hypothesis by showing that although a system may have very high contrast, it may suffer from noise, which iii deteriorates the system's ability to detect fine details. The results and discussion presented here have been published in a journal in hope to inform the NR community of the nuisances associated with noise and suggest that NPS and DQE are used to complement MTF in an attempt to describe the quality of neutron imaging devices.iv Acknowledgments

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“…The performance of the ideal observer in the same experiment can either be measured with a computer simulation or by calculating the SNR from the imaging parameters. The ratio (3) then expresses a statistical efficiency for the real observer and represents the fraction of the information in the image that he extracts in performing it.…”

Section: Performance Of Real Observersmentioning

confidence: 99%

<title>More Unified Analysis Of Medical Imaging System SNR Characteristics</title>

Wagner

Brown

1984

SPIE Proceedings

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The ideal observer signal-to-noise ratio has been derived from statistical decision theory for all of the major medical imaging modalities. This yields an absolute scale for image performance assessment and instrumentation design and optimization. Applications include: the functional dependence of detectable detail size on exposure or imaging time; a framework for comparing data acquisition techniques, e.g., Fourier methods vs reconstruction from projections in NMR imaging; calculations of realizable limits, e.g., the limiting gain of time-of-flight PET scanning. Measurements on human observers show that they can come close to ideal performance, except when the noise has negative correlations as in images reconstructed from projections. In this latter case they suffer a small but significant penalty.

show abstract

Evaluating the efficient of imaging processes

Cited by 46 publications

References 184 publications

Unified SNR analysis of medical imaging systems

Unified SNR analysis of medical imaging systems

Noise evaluation of a digital neutron imaging device

<title>More Unified Analysis Of Medical Imaging System SNR Characteristics</title>

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