Comparison of Two Methods to Develop Breast Models for Simulation of Breast Tomosynthesis and CT

O’Connor, J. Michael; Das, Mini; Didier, Clay; Mahd, Mufeed; Glick, Stephen J.

doi:10.1007/978-3-540-70538-3_58

Cited by 12 publications

(12 citation statements)

References 9 publications

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“…O'Connor et al are creating an ensemble of voxelized breast phantoms that are generated by acquiring CT data of mastectomy specimens placed into holders that shape the excised specimen into an uncompressed or compressed position [82][83][84]. While the simulated images are realistic, the O'Connor's voxelized phantoms have a fixed anatomy and position after they have been generated and lack the flexibility of mathematical phantoms.…”

Section: Voxelized Breast Phantomsmentioning

confidence: 99%

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Three-dimensional computer generated breast phantom based on empirical data

Segars

et al. 2008

SPIE Proceedings

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Breast imaging has improved the early detection of breast cancer thereby decreasing the mortality rate; however, thousands of women are wrongly diagnosed each year.Improving the sensitivity and specificity of breast cancer imaging is an important area of research and development. One of the major hurdles in imaging research arises from the difficulty in accruing human subject data because of cost, time, or patient risk considerations. Consequently, computerized phantoms are an important research tool that can help in developing new imaging techniques and devices. They can simulate a potentially unlimited amount of patient anatomies and provide a known truth with which to quantitatively evaluate, compare, and improve new imaging technologies in a costeffective and efficient method. It is essential for computerized phantoms to be anatomically realistic and produce realistic imaging data such that results from studies utilizing the phantoms are indicative of what would occur in human subjects.The purpose of this dissertation is to develop a three-dimensional computer generated breast phantom that is based on empirical data that can be used in breast imaging research. Currently available breast phantoms are either voxelized phantoms with fixed anatomy or flexible mathematical phantoms based on geometric primitives such as spheres and cylinders. In this work, we present the method to generate a suite of hybrid breast phantoms that combine the realism of a voxelized phantom with the flexibility to easily model anatomical variations by incorporating a mathematical basis.The first step in phantom generation was to acquire and process the imaging data.We received dedicated breast computed tomography imaging data of pendant v uncompressed breasts of human subjects from our collaborators at UC Davis. We implemented pre-and post-reconstruction algorithms to reduce the noise and scatter inherent in the images from the low-dose acquisition of the data and the cone-beam geometry of the CT system, respectively. Following image processing, we developed a custom volumetric segmentation algorithm to differentiate the breast tissues and maintain the high-resolution detail available in the imaging data. Derived from real human data, this step produced an anatomically realistic basis for the breast phantom.Following segmentation, a subdivision surface model of the breast tissue was generated. This step introduced flexibility to the empirically based phantom by using a mathematical description for the breast tissue surfaces as subdivision surface models can be altered using affine or other transformations. This phantom can be used for imaging studies using an uncompressed geometry or it can be used to generate a finite element mesh of the breast to be used for a compression model. Simulated compression of the breast phantom was achieved by applying finite element methods that can realistically deform the phantom. The material properties of the different types of breast tissue were incorporated into this model. Also, a comprehe...

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Section: Voxelized Breast Phantomsmentioning

confidence: 99%

“…These specimens were placed in a special holder and imaged with a prototype bench-top cone beam bCT imaging system [82][83][84]. The group used a commercially available segmentation tool in the Mimics software (Materialise NV, Leuven, Belgium).…”

Section: Dedicated Bct Image Segmentationmentioning

confidence: 99%

Three-dimensional computer generated breast phantom based on empirical data

Segars

et al. 2008

SPIE Proceedings

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“…This presents a potential impediment to the widespread deployment of the VCT paradigm in breast imaging. Previous methods to simulate such breast anatomy have involved using mathematical simulation methods (Bliznakova et al 2003, 2010, Bakic et al 2011, 2014, Graff 2016, Pokrajac et al 2012, patient CT data (Li et al 2009, Kiarashi et al 2016, Ikejimba et al 2016, mastectomy CT data (Hoeschen et al 2005, O'Connor et al 2008 and computer generated noise models (Rolland et al 1997, Bochud et al 1999, Heine et al 1999, Castella et al 2008. However, it is a very challenging task to simulate realistic radiological images calculated using such mathematically derived models, since a proper selection of geometrical parameters of the basic primitives (Bliznakova et al 2003) and reduction of geometric appearance of the border between different tissues (Bakic et al 2011) are required to achieve high levels of clinical realism.…”

Section: Introductionmentioning

confidence: 99%

Design and validation of realistic breast models for use in multiple alternative forced choice virtual clinical trials

et al. 2017

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A novel method has been developed for generating quasi-realistic voxel phantoms which simulate the compressed breast in mammography and digital breast tomosynthesis (DBT). The models are suitable for use in virtual clinical trials requiring realistic anatomy which use the multiple alternative forced choice (AFC) paradigm and patches from the complete breast image. The breast models are produced by extracting features of breast tissue components from digital breast tomosynthesis (DBT) clinical images including skin, adipose and fibro-glandular tissue, blood vessels and Cooper's ligaments. A range of different breast models can then be generated by combining these components. Visual realism was validated using a receiver operating characteristic (ROC) study of patches from simulated images calculated using the breast models and from real patient images. Quantitative analysis was undertaken using fractal dimension and power spectrum analysis. The average areas under the ROC curves for 2D and DBT images were .51±.06 and .54±.09 demonstrating that simulated and real images were statistically indistinguishable by expert breast readers (7 observers); errors represented as one standard error of the mean. The average fractal dimensions (2D, DBT) for real and simulated images were (2.72±.01, 2.75±.01) and (2.77±.03, 2.82±.04) respectively; errors represented as one standard error of the mean. Excellent agreement was found between power spectrum curves of real and simulated images, with average β values (2D, DBT) of (3.10±.17, 3.21±.11) and (3.01±.32, 3.19±.07) respectively; errors represented as one standard error of the mean. These results demonstrate that radiological images of these breast models realistically represent the complexity of real breast structures and can be used to simulate patches from mammograms and DBT images that are indistinguishable from patches from the corresponding real breast images. The method can generate about 500 radiological patches (~30mm x 30mm) per day for AFC experiments on a single workstation. This is the first study to quantitatively validate the realism of simulated radiological breast images using direct blinded comparison with real data via the ROC paradigm with expert breast readers. Page 1 of 16AUTHOR SUBMITTED MANUSCRIPT -PMB-104914. R2 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 KeywordsVirtual clinical trials, breast model, breast phantom, synthetic breast, image simulation, 2D-mammography, digital breast tomosynthesis.

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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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Comparison of Two Methods to Develop Breast Models for Simulation of Breast Tomosynthesis and CT

Cited by 12 publications

References 9 publications

Three-dimensional computer generated breast phantom based on empirical data

Three-dimensional computer generated breast phantom based on empirical data

Design and validation of realistic breast models for use in multiple alternative forced choice virtual clinical trials

Optimized generation of high resolution breast anthropomorphic software phantoms

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