On the statistical nature of mammograms

Heine, John J.; Deans, Stanley R.; Velthuizen, R.P.; Clarke, Laurence P.

doi:10.1118/1.598739

Cited by 76 publications

(83 citation statements)

References 31 publications

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“…37,39,47 These results differ from those reported by Bochud et al 48 that are higher compared to the results of this and other published studies. This is attributed to the use of constant ring width approach and that the authors used the linear part of the fit to estimate the ␤ value.…”

Section: Ivb Objective Evaluationcontrasting

confidence: 57%

Evaluation of an improved algorithm for producing realistic 3D breast software phantoms: Application for mammography

et al. 2010

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Purpose: This work presents an improved algorithm for the generation of 3D breast software phantoms and its evaluation for mammography. Methods: The improved methodology has evolved from a previously presented 3D noncompressed breast modeling method used for the creation of breast models of different size, shape, and composition. The breast phantom is composed of breast surface, duct system and terminal ductal lobular units, Cooper's ligaments, lymphatic and blood vessel systems, pectoral muscle, skin, 3D mammographic background texture, and breast abnormalities. The key improvement is the development of a new algorithm for 3D mammographic texture generation. Simulated images of the enhanced 3D breast model without lesions were produced by simulating mammographic image acquisition and were evaluated subjectively and quantitatively. For evaluation purposes, a database with regions of interest taken from simulated and real mammograms was created. Four experienced radiologists participated in a visual subjective evaluation trial, as they judged the quality of the simulated mammograms, using the new algorithm compared to mammograms, obtained with the old modeling approach. In addition, extensive quantitative evaluation included power spectral analysis and calculation of fractal dimension, skewness, and kurtosis of simulated and real mammograms from the database. Results:The results from the subjective evaluation strongly suggest that the new methodology for mammographic breast texture creates improved breast models compared to the old approach. Calculated parameters on simulated images such as ␤ exponent deducted from the power law spectral analysis and fractal dimension are similar to those calculated on real mammograms. The results for the kurtosis and skewness are also in good coincidence with those calculated from clinical images.Comparison with similar calculations published in the literature showed good agreement in the majority of cases. Conclusions: The improved methodology generated breast models with increased realism compared to the older model as shown in evaluations of simulated images by experienced radiologists. It is anticipated that the realism will be further improved using an advanced image simulator so that simulated images may be used in feasibility studies in mammography.

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Section: Ivb Objective Evaluationcontrasting

confidence: 57%

Evaluation of an improved algorithm for producing realistic 3D breast software phantoms: Application for mammography

et al. 2010

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“…Images of real anatomy, of course, present a mixture of quantum noise and background anatomical structure. The frequency content of the latter has been described in terms of a 1 / f ␤ characteristic-an approach common in 2D mammography [41][42][43] and recently extended to 3D imaging. 22,[44][45][46] Such anatomical NPS may be added to the quantum NPS in "generalized" forms 47,48 of the NEQ and detectability index, typically diminishing the importance of the low-frequency NEQ and causing a greater contribution to task performance from the high-frequency image characteristics.…”

Section: Discussionmentioning

confidence: 99%

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

2008

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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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“…The effect of anatomical background on detectability is a subject of considerable interest, commonly modeling the background as power-law noise j=f b included as an additive noise term in the "generalized" NEQ. For example, in breast imaging, the power-law characteristic in 2D mammographic images was characterized by Bochud et al, 21 Burgess, 22,23 and others 24 and extended to 3D breast imaging by Metheany et al, 25 Engstrom et al, 26 Glick et al, 27 Gong et al, 28 and Reiser and Nishikawa, 29 showing b differs in 2D projections versus 3D tomosynthesis and CBCT reconstructions. In a fairly general context, Gang et al 30 showed power-law background noise to arise from superposition of self-similar (fractal) structures in 2D and 3D images, derived relations between b in projection, tomosynthesis, and CBCT, and incorporated the result in a generalized detectability index.…”

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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On the statistical nature of mammograms

Cited by 76 publications

References 31 publications

Evaluation of an improved algorithm for producing realistic 3D breast software phantoms: Application for mammography

Evaluation of an improved algorithm for producing realistic 3D breast software phantoms: Application for mammography

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

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

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