Solid‐state fluoroscopic imager for high‐resolution angiography: Parallel‐cascaded linear systems analysis

Vedantham, Srinivasan; Karellas, Andrew; Suryanarayanan, Sankararaman

doi:10.1118/1.1689014

Cited by 46 publications

(81 citation statements)

References 49 publications

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“…Additional details can be seen in a number of works. [33][34][35][36][37][38][39][40] Amplification processes may involve binary selection or conversion of quanta from one form to another. The signal at the output of stage i of an amplification process is described by…”

Section: Iia Theoretical Development Of the Noise-response Methodsmentioning

confidence: 99%

“…[37][38][39][40] Careful inspection of the resultant noise response of such systems from a theoretical framework, as described by the two-dimensional noise power spectrum ͑NPS͒, indicates that the resolution response ͑i.e., the MTF͒ is inherently included in such information. 41,42 In this work, we present an exact relationship using a generalized cascaded linear systems analysis.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Iia Theoretical Development Of the Noise-response Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Accurate MTF measurement in digital radiography using noise response

et al. 2010

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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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“…[3][4][5][6][7][8] Such analysis can be extended to simple models of observer performance in terms of taskbased detectability index (d 0 ), 9 which has been shown to demonstrate reasonable correspondence with real observer performance for a variety of simple imaging tasks across a broad range of experimental conditions. 10 A considerable body of previous work established the basis for modeling of CBCT imaging performance.…”

Section: Introductionmentioning

confidence: 99%

Task-based modeling and optimization of a cone-beam CT scanner for musculoskeletal imaging

et al. 2011

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Purpose: This work applies a cascaded systems model for cone-beam CT imaging performance to the design and optimization of a system for musculoskeletal extremity imaging. The model provides a quantitative guide to the selection of system geometry, source and detector components, acquisition techniques, and reconstruction parameters. Methods: The model is based on cascaded systems analysis of the 3D noise-power spectrum (NPS) and noise-equivalent quanta (NEQ) combined with factors of system geometry (magnification, focal spot size, and scatter-to-primary ratio) and anatomical background clutter. The model was extended to task-based analysis of detectability index (d 0 ) for tasks ranging in contrast and frequency content, and d 0 was computed as a function of system magnification, detector pixel size, focal spot size, kVp, dose, electronic noise, voxel size, and reconstruction filter to examine tradeoffs and optima among such factors in multivariate analysis. The model was tested quantitatively versus the measured NPS and qualitatively in cadaver images as a function of kVp, dose, pixel size, and reconstruction filter under conditions corresponding to the proposed scanner. Results: The analysis quantified trade-offs among factors of spatial resolution, noise, and dose. System magnification (M) was a critical design parameter with strong effect on spatial resolution, dose, and x-ray scatter, and a fairly robust optimum was identified at M $ 1.3 for the imaging tasks considered. The results suggested kVp selection in the range of $65-90 kVp, the lower end (65 kVp) maximizing subject contrast and the upper end maximizing NEQ (90 kVp). The analysis quantified fairly intuitive resultse.g., $0.1-0.2 mm pixel size (and a sharp reconstruction filter) optimal for high-frequency tasks (bone detail) compared to $0.4 mm pixel size (and a smooth reconstruction filter) for low-frequency (soft-tissue) tasks. This result suggests a specific protocol for 1 Â 1 (full-resolution) projection data acquisition followed by full-resolution reconstruction with a sharp filter for high-frequency tasks along with 2 Â 2 binning reconstruction with a smooth filter for low-frequency tasks. The analysis guided selection of specific source and detector components implemented on the proposed scanner. The analysis also quantified the potential benefits and points of diminishing return in focal spot size, reduced electronic noise, finer detector pixels, and low-dose limits of detectability. Theoretical results agreed quantitatively with the measured NPS and qualitatively with evaluation of cadaver images by a musculoskeletal radiologist. Conclusions: A fairly comprehensive model for 3D imaging performance in cone-beam CT combines factors of quantum noise, system geometry, anatomical background, and imaging task. The analysis provided a valuable, quantitative guide to design, optimization, and technique selection for a musculoskeletal extremities imaging system under development.

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Solid‐state fluoroscopic imager for high‐resolution angiography: Parallel‐cascaded linear systems analysis

Cited by 46 publications

References 49 publications

Accurate MTF measurement in digital radiography using noise response

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

Task-based modeling and optimization of a cone-beam CT scanner for musculoskeletal imaging

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