An Anthropomorphic Breast Model for Breast Imaging Simulation and Optimization

Chen, Baiyu; Shorey, Jamie Margaret; Saunders, R. S.; Richard, Samuel; Thompson, John D.; Nolte, L. W.; Samei, Ehsan

doi:10.1016/j.acra.2010.11.009

Cited by 50 publications

(48 citation statements)

References 20 publications

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“…"Clutter phantoms"-popular in the last decade for simulating the anatomical power spectrum in applications such as breast CBCT (Refs. [38][39][40]-are considerably better suited to such measurement, and a collection of spheres of varying diameter and contrast [providing an approximation to noise of the form 1/f 3 associated with a self-similar object (3D fractal)] was shown to provide a good, statistically motivated phantom for physically probing such sampling effects. 12 Further consideration involves the effect of redundant rays on the noise and NPS as shown in Fig.…”

Section: -9mentioning

confidence: 99%

Noise, sampling, and the number of projections in cone-beam CT with a flat-panel detector

Zhao

Gang

Siewerdsen³

2014

Med. Phys.

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Purpose:To investigate the effect of the number of projection views on image noise in cone-beam CT (CBCT) with a flat-panel detector. Methods: This fairly fundamental consideration in CBCT system design and operation was addressed experimentally (using a phantom presenting a uniform medium as well as statistically motivated "clutter") and theoretically (using a cascaded systems model describing CBCT noise) to elucidate the contributing factors of quantum noise (σ Q ), electronic noise (σ E ), and view aliasing (σ view ). Analysis included investigation of the noise, noise-power spectrum, and modulation transfer function as a function of the number of projections (N proj ), dose (D tot ), and voxel size (b vox ). Results:The results reveal a nonmonotonic relationship between image noise and N proj at fixed total dose: for the CBCT system considered, noise decreased with increasing N proj due to reduction of view sampling effects in the regime N proj <∼200, above which noise increased with N proj due to increased electronic noise. View sampling effects were shown to depend on the heterogeneity of the object in a direct analytical relationship to power-law anatomical clutter of the form κ/f β -and a general model of individual noise components (σ Q , σ E , and σ view ) demonstrated agreement with measurements over a broad range in N proj , D tot , and b vox . Conclusions:The work elucidates fairly basic elements of CBCT noise in a manner that demonstrates the role of distinct noise components (viz., quantum, electronic, and view sampling noise). For configurations fairly typical of CBCT with a flat-panel detector (FPD), the analysis reveals a "sweet spot" (i.e., minimum noise) in the range N proj ∼ 250-350, nearly an order of magnitude lower in N proj than typical of multidetector CT, owing to the relatively high electronic noise in FPDs. The analysis explicitly relates view aliasing and quantum noise in a manner that includes aspects of the object ("clutter") and imaging chain (including nonidealities of detector blur and electronic noise) to provide a more rigorous basis for commonly held intuition and heurism in CBCT system design and operation.

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Section: -9mentioning

confidence: 99%

Noise, sampling, and the number of projections in cone-beam CT with a flat-panel detector

Zhao

Gang

Siewerdsen³

2014

Med. Phys.

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“…2 Power-law backgrounds have been widely used as a statistical model for breast backgrounds, [3][4][5][6][7][8][9] and power-law exponents in clinical tomosynthesis and breast CT images have been investigated. 10,11 To date, power-law coefficients have been estimated from the radial averaged of the power spectrum.…”

Section: Introductionmentioning

confidence: 99%

On the orientation of mammographic structure

2011

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Purpose: Burgess et al. have shown that the power-spectral density of mammographic breast tissue P(f) follows a power-law, P(f) ¼ c=f b . 1 Due to the complexity of the breast anatomy, breast phantoms often make use of power-law backgrounds to approximate the irregular texture of breast images. However, the current methodology of estimating power-law coefficients assumes that the breast structure is isotropic. The purpose of this letter is to demonstrate that breast anatomic structure is not isotropic, but in fact has a preferred orientation. Further, we present a formalism to estimate power-law coefficients b and c while accounting for tissue orientation in mammographic regions-of-interests (ROIs). We then show the effect of structure orientation on b and c, as well as on the appearance of simulated power-law backgrounds. Methods: When breast tissue exhibits a preferred orientation, the radial symmetry in the associated power spectrum is broken. The new symmetry was fit by an ellipsoidal model. Ellipse tilt angle and axis ratio were accounted for in the power-law fit. Results: On average, breast structure was found to point toward the nipple: the average orientation in MLO views was 22.5 , while it was 5 for CC views, and the mean orientation for left breasts was negative while it was positive for right breasts. For both power-law magnitude and exponent, the mean difference was statistically significant ( ¼ À0.096, ¼À0.192). Conclusions: A formalism for quantification of breast structure and structure orientation is provided. The difference in power-law coefficient estimates when accounting for orientation was found to be statistically significant. Examples of statistically defined backgrounds indicate that breast structure is mimicked more closely when structure orientation is accounted for.

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“…With the advent of three-dimensional imaging modalities and the decreasing cost of computer memory, it has become essential and feasible to create these multi-gigabyte arrays for the purpose of mimicking tissue in simulation studies. Many groups are working on creating breast phantoms, including ones based on mastectomy specimens [13], breast CT images [14], and entirely computer-generated models [15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Breast Tomosynthesis Imaging Systems for Computer-Aided Detection

Lau¹

2011

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Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. REPORT DATE (DD-MM-YYYY)2 The goal of this research is to develop methodology for optimizing acquisition parameters for digital tomosynthesis of the breast (DBT). Optimization is important to be able to study whether DBT can be used in place of screening mammography with better sensitivity and specificity. The research is composed of three parts: 1) to develop a computer model to simulate tomosynthesis, 2) to generate realistic breast and tumor models, and 3) to determine optimal acquisition parameters by using a genetic algorithm with CADe performance as an indicator of fitness. In this report, we summarize the research done for this project to date, focussing particularly on the development of an anthropomorphic software breast phantom and its validation. Lastly, we evaluate methods for measuring anatomic noise in projection imaging.Digital breast tomosynthesis, optimization, computer simulation, anatomic noise, anthropomorphic breast phantom 30

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An Anthropomorphic Breast Model for Breast Imaging Simulation and Optimization

Cited by 50 publications

References 20 publications

Noise, sampling, and the number of projections in cone-beam CT with a flat-panel detector

Noise, sampling, and the number of projections in cone-beam CT with a flat-panel detector

On the orientation of mammographic structure

Optimization of Breast Tomosynthesis Imaging Systems for Computer-Aided Detection

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