Three-dimensional computer generated breast phantom based on empirical data

Li, Christina M.; Segars, W. Paul; Lo, Joseph Y.; Veress, Alexander I.; Boone, John M.; Dobbins, James T.

doi:10.1117/12.772185

Cited by 7 publications

(9 citation statements)

References 91 publications

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“…[31][32][33] The segmented datasets of two different human subjects were used as the "base" and "target" for deformation and morphing to generate new morphed data. The segmented datasets consisted of 300 coronal slices (each 384 × 384 voxels) with 500 μm isotropic resolution and contained three different tissue types: fat, glandular, and skin.…”

Section: Methodsmentioning

confidence: 99%

“…They are based on dedicated breast computed tomography datasets (bCT) of human subjects, [2][3][4] thus encompassing the variability and complexity of real human anatomy, and by using computer-graphics techniques they also have the flexibility intrinsic in a mathematical phantom. [31][32][33]43 However, to date, these phantoms have been based on a small cohort of human subjects, constraining the breast variability that an imaging phantom ideally possesses. The goal of this current effort was to utilize image morphing in order to generate multiple realistic phantoms from a limited set of bCT data.…”

Section: Introductionmentioning

confidence: 99%

“…The phantoms include a realistic compression simulation model and are capable of simulating multimodality imaging data. [31][32][33][42][43][44][45] The computerized breast phantoms generated from our project are a hybrid of the two phantom generation techniques, combining empirical data with flexible computer graphics techniques. They are based on dedicated breast computed tomography datasets (bCT) of human subjects, [2][3][4] thus encompassing the variability and complexity of real human anatomy, and by using computer-graphics techniques they also have the flexibility intrinsic in a mathematical phantom.…”

Section: Introductionmentioning

confidence: 99%

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Generation of a suite of 3D computer‐generated breast phantoms from a limited set of human subject data

et al. 2013

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Purpose:The authors previously reported on a three-dimensional computer-generated breast phantom, based on empirical human image data, including a realistic finite-element based compression model that was capable of simulating multimodality imaging data. The computerized breast phantoms are a hybrid of two phantom generation techniques, combining empirical breast CT (bCT) data with flexible computer graphics techniques. However, to date, these phantoms have been based on single human subjects. In this paper, the authors report on a new method to generate multiple phantoms, simulating additional subjects from the limited set of original dedicated breast CT data. The authors developed an image morphing technique to construct new phantoms by gradually transitioning between two human subject datasets, with the potential to generate hundreds of additional pseudoindependent phantoms from the limited bCT cases. The authors conducted a preliminary subjective assessment with a limited number of observers (n = 4) to illustrate how realistic the simulated images generated with the pseudoindependent phantoms appeared. Methods: Several mesh-based geometric transformations were developed to generate distorted breast datasets from the original human subject data. Segmented bCT data from two different human subjects were used as the "base" and "target" for morphing. Several combinations of transformations were applied to morph between the "base' and "target" datasets such as changing the breast shape, rotating the glandular data, and changing the distribution of the glandular tissue. Following the morphing, regions of skin and fat were assigned to the morphed dataset in order to appropriately assign mechanical properties during the compression simulation. The resulting morphed breast was compressed using a finite element algorithm and simulated mammograms were generated using techniques described previously. Sixty-two simulated mammograms, generated from morphing three human subject datasets, were used in a preliminary observer evaluation where four board certified breast radiologists with varying amounts of experience ranked the level of realism (from 1 = "fake" to 10 = "real") of the simulated images. Results: The morphing technique was able to successfully generate new and unique morphed datasets from the original human subject data. The radiologists evaluated the realism of simulated mammograms generated from the morphed and unmorphed human subject datasets and scored the realism with an average ranking of 5.87 ± 1.99, confirming that overall the phantom image datasets appeared more "real" than "fake." Moreover, there was not a significant difference (p > 0.1) between the realism of the unmorphed datasets (6.0 ± 1.95) compared to the morphed datasets (5.86 ± 1.99). Three of the four observers had overall average rankings of 6.89 ± 0.89, 6.9 ± 1.24, 6.76 ± 1.22, whereas the fourth observer ranked them noticeably lower at 2.94 ± 0.7. Conclusions: This work presents a technique that can be used to generate a suite of realistic...

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Generation of a suite of 3D computer‐generated breast phantoms from a limited set of human subject data

et al. 2013

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“…The details of this algorithm have been presented in detail previously, but in general, the breast is compressed in one dimension ͑x͒ and extended in the other dimensions ͑y and z͒ simulating compression between stiff plates. 46 The breast is assumed to be incompressible ͑fixed volume͒ and isotropic. The mesh's node locations were determined to be inside or outside the compressed thickness of the breast.…”

Section: Iie Simulated Compressionmentioning

confidence: 99%

“…46 Attenuation coefficients for adipose, fibroglandular, and skin were derived from International Commission on Radiation Units and Measurements ͑ICRU͒ tissue data. 47 The three different levels of fibroglandular tissue were assigned attenuation coefficients between adipose and muscle in order to account for their relative amount of marbling.…”

Section: Iif Simulated Radiographic Imagesmentioning

confidence: 99%

Methodology for generating a 3D computerized breast phantom from empirical data

Li¹,

Segars²,

Tourassi³

et al. 2009

Medical Physics

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116

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The initial process for creating a flexible three-dimensional computer-generated breast phantom based on empirical data is described. Dedicated breast computed-tomography data were processed to suppress noise and scatter artifacts in the reconstructed image set. An automated algorithm was developed to classify the breast into its primary components. A preliminary phantom defined using subdivision surfaces was generated from the segmented data. To demonstrate potential applications of the phantom, simulated mammographic image data were acquired of the phantom using a simplistic compression model and an analytic projection algorithm directly on the surface model. The simulated image was generated using a model for a polyenergetic cone-beam projection of the compressed phantom. The methods used to create the breast phantom generate resulting images that have a high level of tissue structure detail available and appear similar to actual mammograms. Fractal dimension measurements of simulated images of the phantom are comparatively similar to measurements from images of real human subjects. A realistic and geometrically defined breast phantom that can accurately simulate imaging data may have many applications in breast imaging research.

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Application of a Dynamic 4D Anthropomorphic Breast Phantom in Contrast-Based Imaging System Optimization: Dual-Energy or Temporal Subtraction?

Kiarashi

Ghate

et al. 2012

Breast Imaging

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Three-dimensional computer generated breast phantom based on empirical data

Cited by 7 publications

References 91 publications

Generation of a suite of 3D computer‐generated breast phantoms from a limited set of human subject data

Generation of a suite of 3D computer‐generated breast phantoms from a limited set of human subject data

Methodology for generating a 3D computerized breast phantom from empirical data

Application of a Dynamic 4D Anthropomorphic Breast Phantom in Contrast-Based Imaging System Optimization: Dual-Energy or Temporal Subtraction?

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