Development of an Analytic Breast Phantom for Quantitative Comparison of Reconstruction Algorithms for Digital Breast Tomosynthesis

Reiser, Ingrid; Sidky, Emil Y.; Nishikawa, Robert M.; Pan, Xiaochuan

doi:10.1007/11783237_27

Cited by 14 publications

(10 citation statements)

References 6 publications

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“…The simulated projection images were added to 2D real or simulated mammographic backgrounds, thus creating a visually realistic appearance. Reiser et al (2006) constructed a 3D analytical breast phantom consisting of ellipsoids, both full and truncated. Bakic et al (2002) designed a 3D phantom composed of large scale structures mod- Fig.…”

Section: Previous Workmentioning

confidence: 99%

Task-based performance analysis of FBP, SART and ML for digital breast tomosynthesis using signal CNR and Channelised Hotelling Observers

Sompel

Brady

Boone

2011

Medical Image Analysis

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Section: Previous Workmentioning

confidence: 99%

Task-based performance analysis of FBP, SART and ML for digital breast tomosynthesis using signal CNR and Channelised Hotelling Observers

Sompel

Brady

Boone

2011

Medical Image Analysis

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“…[19][20][21][22][23][24][25] We needed three specific features in a software phantom: (1) the ability to generate random breast parenchymal patterns, (2) projection image statistics that match mammogram statistics, and (3) the ability to generate a large batch of phantoms relatively quickly. Bakic's voxelized breast phantom model was chosen to meet these requirements.…”

Section: Iia the Digital Phantom Ensemblementioning

confidence: 99%

A virtual trial framework for quantifying the detectability of masses in breast tomosynthesis projection data

et al. 2013

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Purpose: Digital breast tomosynthesis (DBT) is a promising breast cancer screening tool that has already begun making inroads into clinical practice. However, there is ongoing debate over how to quantitatively evaluate and optimize these systems, because different definitions of image quality can lead to different optimal design strategies. Powerful and accurate tools are desired to extend our understanding of DBT system optimization and validate published design principles. Methods: The authors developed a virtual trial framework for task-specific DBT assessment that uses digital phantoms, open-source x-ray transport codes, and a projection-space, spatial-domain observer model for quantitative system evaluation. The authors considered evaluation of reconstruction algorithms as a separate problem and focused on the information content in the raw, unfiltered projection images. Specifically, the authors investigated the effects of scan angle and number of angular projections on detectability of a small (3 mm diameter) signal embedded in randomly-varying anatomical backgrounds. Detectability was measured by the area under the receiver-operating characteristic curve (AUC). Experiments were repeated for three test cases where the detectability-limiting factor was anatomical variability, quantum noise, or electronic noise. The authors also juxtaposed the virtual trial framework with other published studies to illustrate its advantages and disadvantages. Results: The large number of variables in a virtual DBT study make it difficult to directly compare different authors' results, so each result must be interpreted within the context of the specific virtual trial framework. The following results apply to 25% density phantoms with 5.15 cm compressed thickness and 500 μm 3 voxels (larger 500 μm 2 detector pixels were used to avoid voxel-edge artifacts): 1. For raw, unfiltered projection images in the anatomical-variability-limited regime, AUC appeared to remain constant or increase slightly with scan angle. 2. In the same regime, when the authors fixed the scan angle, AUC increased asymptotically with the number of projections. The threshold number of projections for asymptotic AUC performance depended on the scan angle. In the quantum-and electronic-noise dominant regimes, AUC behaviors as a function of scan angle and number of projections sometimes differed from the anatomy-limited regime. For example, with a fixed scan angle, AUC generally decreased with the number of projections in the electronic-noise dominant regime. These results are intended to demonstrate the capabilities of the virtual trial framework, not to be used as optimization rules for DBT. Conclusions:The authors have demonstrated a novel simulation framework and tools for evaluating DBT systems in an objective, task-specific manner. This framework facilitates further investigation of image quality tradeoffs in DBT.

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“…Iterative algorithms tend to provide less artifacts in the reconstructed images based on an initial study. 14 There have been a number of studies investigating the effect of tomosynthesis acquisition parameters on image quality. Ren et al 6 investigated the effect of number of projection views on contrast-to-noise ratio ͑CNR͒ for a fixed dose and 20°angular scan using simulated data and data acquired on a tomosynthesis prototype.…”

Section: Introductionmentioning

confidence: 99%

Task-based assessment of breast tomosynthesis: Effect of acquisition parameters and quantum noisea)

2010

Self Cite

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Purpose: Tomosynthesis is a promising modality for breast imaging. The appearance of the tomosynthesis reconstructed image is greatly affected by the choice of acquisition and reconstruction parameters. The purpose of this study was to investigate the limitations of tomosynthesis breast imaging due to scan parameters and quantum noise. Tomosynthesis image quality was assessed based on performance of a mathematical observer model in a signal-known exactly ͑SKE͒ detection task. Methods: SKE detectability ͑dЈ͒ was estimated using a prewhitening observer model. Structured breast background was simulated using filtered noise. Detectability was estimated for designer nodules ranging from 0.05 to 0.8 cm in diameter. Tomosynthesis slices were reconstructed using iterative maximum-likelihood expectation-maximization. The tomosynthesis scan angle was varied between 15°and 60°, the number of views between 11 and 41 and the total number of x-ray quanta was ϱ, 6ϫ 10 5 , and 6 ϫ 10 4 . Detectability in tomosynthesis was compared to that in a single projection. Results: For constant angular sampling distance, increasing the angular scan range increased detectability for all signal sizes. Large-scale signals were little affected by quantum noise or angular sampling. For small-scale signals, quantum noise and insufficient angular sampling degraded detectability. At high quantum noise levels, angular step size of 3°or below was sufficient to avoid image degradation. At lower quantum noise levels, increased angular sampling always resulted in increased detectability. The ratio of detectability in the tomosynthesis slice to that in a single projection exhibited a peak that shifted to larger signal sizes when the angular range increased. For a given angular range, the peak shifted toward smaller signals when the number of views was increased. The ratio was greater than unity for all conditions evaluated. Conclusion: The effect of acquisition parameters on lesion detectability depends on signal size. Tomosynthesis scan angle had an effect on detectability for all signals sizes, while quantum noise and angular sampling only affected the detectability small-scale signals.

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Development of an Analytic Breast Phantom for Quantitative Comparison of Reconstruction Algorithms for Digital Breast Tomosynthesis

Cited by 14 publications

References 6 publications

Task-based performance analysis of FBP, SART and ML for digital breast tomosynthesis using signal CNR and Channelised Hotelling Observers

Task-based performance analysis of FBP, SART and ML for digital breast tomosynthesis using signal CNR and Channelised Hotelling Observers

A virtual trial framework for quantifying the detectability of masses in breast tomosynthesis projection data

Task-based assessment of breast tomosynthesis: Effect of acquisition parameters and quantum noisea)

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