Quantum noise in digital X-ray image detectors with optically coupled scintillators

Flynn, Michael J.; Hames, Sean M.; Wilderman, S.J.; Ciarelli, James J.

doi:10.1109/23.531897

Cited by 18 publications

(7 citation statements)

References 19 publications

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“…The simulations presented here do not take account of the direct absorption of x rays by the detector. Such "direct hits" can add significant noise to an image because of the large amount of charge released per interaction, 40 and can also lead to cumulative damage of the semiconductors. It is expected that this will be much less important in organic semiconductors on plastic substrates due to the much lower inter- action probability in both the substrate and the semiconductor.…”

Section: Ivb Modeling Resultsmentioning

confidence: 99%

Modeling the imaging performance of prototype organic x‐ray imagers

Blakesley

Speller

2007

Medical Physics

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A unified Monte Carlo and cascaded systems model for the simulation of active-matrix flat-panel imagers is presented. With few input parameters, the model simulated the imaging performance of previously measured flat-panel imagers with reasonable accuracy. The model is used to predict the properties of conceptual flat-panel imagers based on organic semiconductors on plastic substrates. The model suggests that significant improvements in resolution and detective quantum efficiency could be achieved by operating such a detector in a back-side illuminated configuration, or by employing two imaging arrays arranged face-to-face. The effect of semiconductor properties on the conceptual imagers is investigated. According to the model, a photodiode quantum efficiency of 25% and dark current of less than 100 pA mm(-2) would be satisfactory for a prototype imager, while a competitive imager would require a photodiode quantum efficiency of 40-50% with a dark current of less than 10 pA mm(-2) to be quantum limited over the radiographic exposure range.

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Section: Ivb Modeling Resultsmentioning

confidence: 99%

Modeling the imaging performance of prototype organic x‐ray imagers

Blakesley

Speller

2007

Medical Physics

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“…There is a noise present in dental images, as one can see from these fragments, that might partly mask important diagnostic information. This noise arises due to a limited time of imaging the object, and properties of noise are complex [29,31,38]. In the simplest case, one can model noise in dental images as Poisson-like signal dependent [29].…”

Section: Some Assumptions On Image/noise Propertiesmentioning

confidence: 99%

“…This noise arises due to a limited time of imaging the object, and properties of noise are complex [29,31,38]. In the simplest case, one can model noise in dental images as Poisson-like signal dependent [29]. However, more detailed analysis shows that it is, in general, signal dependent but has more complex nature.…”

Section: Some Assumptions On Image/noise Propertiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Medical images, in general, and dental images, in particular, can be corrupted by a noise [28][29][30], which can be seen well in the visualized data. Noise properties depend on many factors and, in general, are not purely additive and white [29][30][31]. Moreover, a lossy image compression had several peculiarities discovered in [32,33] and was considered later in the literature [34,35].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Fast Method of Visually Lossless Compression of Dental Images

et al. 2020

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A noniterative approach to the problem of visually lossless compression of dental images is proposed for an image coder based on the discrete cosine transform (DCT) and partition scheme optimization. This approach considers the following peculiarities of the problem. It is necessary to carry out lossy compression of dental images to achieve large compression ratios (CRs). Since dental images are viewed and analyzed by specialists, it is important to preserve useful diagnostic information preventing appearance of any visible artifacts due to lossy compression. At last, dental images may contain noise having complex statistical and spectral properties. In this paper, we have analyzed and utilized dependences of three quality metrics (Peak signal-to-noise ratio, PSNR; eak Signal-to-Noise Ratio using Human Visual System and Masking (PSNR-HVS-M); and feature similarity, FSIM) on the quantization step (QS), which controls a compression ratio for the so-called advanced DCT coder (ADCTC). The threshold values of distortion visibility for these metrics have been considered. Finally, the recent results on detectable changes in noise intensity have been incorporated in the QS setting. A visual comparison of original and compressed images allows to conclude that the introduced distortions are practically undetectable for the proposed approach; meanwhile, the provided CR lies within the interval.

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Fabrication and application of customized breast phantom for MMWF noise reduction algorithm in digital mammography: An experimental study

Park

2022

Optik

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Quantum noise in digital X-ray image detectors with optically coupled scintillators

Cited by 18 publications

References 19 publications

Modeling the imaging performance of prototype organic x‐ray imagers

Modeling the imaging performance of prototype organic x‐ray imagers

A Fast Method of Visually Lossless Compression of Dental Images

Fabrication and application of customized breast phantom for MMWF noise reduction algorithm in digital mammography: An experimental study

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