A three-dimensional breast software phantom for mammography simulation

Bliznakova, Kristina; Bliznakov, Zhivko; Bravou, Vasiliki; Kolitsi, Z.; Pallikarakis, N.

doi:10.1088/0031-9155/48/22/006

Cited by 141 publications

(112 citation statements)

References 39 publications

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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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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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“…While in x-ray mammography a number of breast phantoms have been defined, 38,39 these are typically too complex and some of the structures are not well differentiated by ultrasound or are irrelevant for this modality. We therefore designed a specific digital anthropomorphic breast phantom for ultrasound.…”

Section: Uct Breast Phantomsmentioning

confidence: 99%

Refraction corrected transmission ultrasound computed tomography for application in breast imaging

Jackowski

Dione³

et al. 2010

Medical Physics

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Purpose:We present an iterative framework for CT reconstruction from transmission ultrasound data which accurately and efficiently models the strong refraction effects that occur in our target application: Imaging the female breast. Methods: Our refractive ray tracing framework has its foundation in the fast marching method ͑FNMM͒ and it allows an accurate as well as efficient modeling of curved rays. We also describe a novel regularization scheme that yields further significant reconstruction quality improvements. A final contribution is the development of a realistic anthropomorphic digital breast phantom based on the NIH Visible Female data set. Results: Our system is able to resolve very fine details even in the presence of significant noise, and it reconstructs both sound speed and attenuation data. Excellent correspondence with a traditional, but significantly more computationally expensive wave equation solver is achieved. Conclusions: Apart from the accurate modeling of curved rays, decisive factors have also been our regularization scheme and the high-quality interpolation filter we have used. An added benefit of our framework is that it accelerates well on GPUs where we have shown that clinical 3D reconstruction speeds on the order of minutes are possible.

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“…These simulation methods can be divided into two major categories: (i) methods based upon rules for generating anatomical structures in the breast [1][2][3][4][5][6][7][8] and (ii) methods based upon individual clinical 3D breast images. [9][10][11] These two categories of methods are complementary; while the second category offers an increased level of realism due to the use of clinical data, the first category offers more flexibility to cover clinically observed variations in breast anatomy.…”

Section: Introductionmentioning

confidence: 99%

Optimized generation of high resolution breast anthropomorphic software phantoms

2012

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Purpose: The authors present an efficient method for generating anthropomorphic software breast phantoms with high spatial resolution. Employing the same region growing principles as in their previous algorithm for breast anatomy simulation, the present method has been optimized for computational complexity to allow for fast generation of the large number of phantoms required in virtual clinical trials of breast imaging. Methods: The new breast anatomy simulation method performs a direct calculation of the Cooper's ligaments (i.e., the borders between simulated adipose compartments). The calculation corresponds to quadratic decision boundaries of a maximum a posteriori classifier. The method is multiscale due to the use of octree-based recursive partitioning of the phantom volume. The method also provides user-control of the thickness of the simulated Cooper's ligaments and skin. Results: Using the proposed method, the authors have generated phantoms with voxel size in the range of (25-1000 lm)

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A three-dimensional breast software phantom for mammography simulation

Cited by 141 publications

References 39 publications

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

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

Refraction corrected transmission ultrasound computed tomography for application in breast imaging

Optimized generation of high resolution breast anthropomorphic software phantoms

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