Effects of characteristic x rays on the noise power spectra and detective quantum efficiency of photoconductive x‐ray detectors

The physical factors that govern 2D and 3D imaging performance may be understood from quantitative analysis of the spatial-frequency-dependent signal and noise transfer characteristics ͓e.g., modulation transfer function ͑MTF͒, noise-power spectrum ͑NPS͒, detective quantum efficiency ͑DQE͒, and noise-equivalent quanta ͑NEQ͔͒ along with a task-based assessment of performance ͑e.g., detectability index͒. This paper advances a theoretical framework based on cascaded systems analysis for calculation of such metrics in cone-beam CT ͑CBCT͒. The model considers the 2D projection NPS propagated through a series of reconstruction stages to yield the 3D NPS and allows quantitative investigation of tradeoffs in image quality associated with acquisition and reconstruction techniques. While the mathematical process of 3D image reconstruction is deterministic, it is shown that the process is irreversible, the associated reconstruction parameters significantly affect the 3D DQE and NEQ, and system optimization should consider the full 3D imaging chain. Factors considered in the cascade include: system geometry; number of projection views; logarithmic scaling; ramp, apodization, and interpolation filters; 3D back-projection; and 3D sampling ͑noise aliasing͒. The model is validated in comparison to experiment across a broad range of dose, reconstruction filters, and voxel sizes, and the effects of 3D noise correlation on detectability are explored. The work presents a model for the 3D NPS, DQE, and NEQ of CBCT that reduces to conventional descriptions of axial CT as a special case and provides a fairly general framework that can be applied to the design and optimization of CBCT systems for various applications.

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“…[2][3][4][5][6][7][8][9][10][11][12] The basic concepts and derivation of the 2D projection NPS are briefly summarized below.…”

Section: Iia Background: Cascaded Linear Systems Analysismentioning

confidence: 99%

Cascaded systems analysis of the 3D noise transfer characteristics of flat‐panel cone‐beam CT

2008

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“…Parallel events may occur ͑depending on the x-ray energy and phosphor͒ as a result of the production of secondary x rays. 46,47 The signal and NPS at the output of stage 2 can be written as 38 ⌽ 2 ͑u,v͒ = g 1 ⌽ 0 T 2 ͑u,v͒W…”

Section: Iia2 Stage 2 X-ray-to-light Conversionmentioning

confidence: 99%

Accurate MTF measurement in digital radiography using noise response

et al. 2010

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Purpose:The authors describe a new technique to determine the system presampled modulation transfer function ͑MTF͒ in digital radiography using only the detector noise response. Methods: A cascaded-linear systems analysis was used to develop an exact relationship between the two-dimensional noise power spectrum ͑NPS͒ and the presampled MTF for a generalized detector system. This relationship was then utilized to determine the two-dimensional presampled MTF. For simplicity, aliasing of the correlated noise component of the NPS was assumed to be negligible. Accuracy of this method was investigated using simulated images from a simple detector model in which the "true" MTF was known exactly. Measurements were also performed on three detector technologies ͑an x-ray image intensifier, an indirect flat panel detector, and a solid state x-ray image intensifier͒, and the results were compared using the standard edge-response method. Flat-field and edge images were acquired and analyzed according to guidelines set forth by the International Electrotechnical Commission, using the RQA 5 spectrum. Results: The presampled MTF determined using the noise-response method for the simulated detector system was in close agreement with the true MTF with an averaged percent difference of 0.3% and a maximum difference of 1.1% observed at the Nyquist frequency ͑f N ͒. The edgeresponse method of the simulated detector system also showed very good agreement at lower spatial frequencies ͑less than 0.5 f N ͒ with an averaged percent difference of 1.6% but showed significant discrepancies at higher spatial frequencies ͑greater than 0.5 f N ͒ with an averaged percent difference of 17%. Discrepancies were in part a result of noise in the edge image and phasing errors. For all three detector systems, the MTFs obtained using the two methods were found to be in good agreement at spatial frequencies less than 0.5 f N with an averaged percent difference of 3.4%. Above 0.5 f N , differences increased to an average of 20%. Deviations of the experimental results largely followed the trend seen in the simulation results, suggesting that differences between the two methods could be explained as resulting from the inherent inaccuracies of the edgeresponse measurement technique used in this study. Aliasing of the correlated noise component was shown to have a minimal effect on the measured MTF for the three detectors studied. Systems with significant aliasing of the correlated noise component ͑e.g., a-Se based detectors͒ would likely require a more sophisticated fitting scheme to provide accurate results. Conclusions: Results indicate that the noise-response method, a simple technique, can be used to accurately measure the MTF of digital x-ray detectors, while alleviating the problems and inaccuracies associated with use of precision test objects, such as a slit or an edge.

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“…These descriptors have become common for 2D imaging systems, may be determined by experimental measurements 1,2 and by theoretical calculations ͑e.g., cascaded systems analysis͒, [3][4][5] and have been proven useful in system design and optimization. [6][7][8][9][10][11][12][13][14][15][16][17] These metrics can be described similar to 3D imaging, including tomosynthesis and CBCT. [18][19][20][21][22][23][24][25] With a knowledge of the imaging task and an appropriate model observer, these metrics can be extended to a description of task performance as described by ICRU Report No.…”

Section: Introductionmentioning

confidence: 99%

Noise aliasing and the 3D NEQ of flat-panel cone-beam CT: Effect of 2D/3D apertures and sampling

Tward

Siewerdsen

2009

Med. Phys.

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The ability to tune an imaging system to be optimal for a specific task is an essential component of image quality. This article discusses the ability to tune the noise-equivalent quanta ͑NEQ͒ of cone-beam computed tomography ͑CBCT͒ by managing noise aliasing through binning of data at different points in the reconstruction cascade. The noise power spectrum, modulation transfer function, and NEQ for CBCT are calculated using cascaded systems analysis. Binning is treated as a modular process, insertable between any two stages ͑in both the 2D projection domain and in the 3D reconstruction domain͒, consisting of the application of an aperture, followed by the resampling of data ͑which introduces noise aliasing͒. Several conditions were examined to demonstrate the validity of the model and to describe the effect on the image quality of some common reconstruction and visualization techniques. It was found that when downsampling data for increased reconstruction speed, binning in 2D results in a superior low-frequency NEQ, while binning in 3D results in a superior high-frequency NEQ. Furthermore, visualization procedures such as slice averaging were found not to degrade the NEQ provided the sampling interval is unchanged. Finally methods for reducing noise aliasing by oversampling are examined, and a method to eliminate noise aliasing without increasing reconstruction time is proposed. These results demonstrate the ease with which the NEQ of CBCT can be modified and thus optimized for specific tasks and show how such analysis can be used to improve image quality.

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Effects of characteristic x rays on the noise power spectra and detective quantum efficiency of photoconductive x‐ray detectors

Cited by 59 publications

References 30 publications

Cascaded systems analysis of the 3D noise transfer characteristics of flat‐panel cone‐beam CT

Cascaded systems analysis of the 3D noise transfer characteristics of flat‐panel cone‐beam CT

Accurate MTF measurement in digital radiography using noise response

Noise aliasing and the 3D NEQ of flat-panel cone-beam CT: Effect of 2D/3D apertures and sampling

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