Literature DB >> 22755718

A statistically defined anthropomorphic software breast phantom.

Beverly A Lau1, Ingrid Reiser, Robert M Nishikawa, Predrag R Bakic.   

Abstract

PURPOSE: Digital anthropomorphic breast phantoms have emerged in the past decade because of recent advances in 3D breast x-ray imaging techniques. Computer phantoms in the literature have incorporated power-law noise to represent glandular tissue and branching structures to represent linear components such as ducts. When power-law noise is added to those phantoms in one piece, the simulated fibroglandular tissue is distributed randomly throughout the breast, resulting in dense tissue placement that may not be observed in a real breast. The authors describe a method for enhancing an existing digital anthropomorphic breast phantom by adding binarized power-law noise to a limited area of the breast.
METHODS: Phantoms with (0.5 mm)(3) voxel size were generated using software developed by Bakic et al. Between 0% and 40% of adipose compartments in each phantom were replaced with binarized power-law noise (β = 3.0) ranging from 0.1 to 0.6 volumetric glandular fraction. The phantoms were compressed to 7.5 cm thickness, then blurred using a 3 × 3 boxcar kernel and up-sampled to (0.1 mm)(3) voxel size using trilinear interpolation. Following interpolation, the phantoms were adjusted for volumetric glandular fraction using global thresholding. Monoenergetic phantom projections were created, including quantum noise and simulated detector blur. Texture was quantified in the simulated projections using power-spectrum analysis to estimate the power-law exponent β from 25.6 × 25.6 mm(2) regions of interest.
RESULTS: Phantoms were generated with total volumetric glandular fraction ranging from 3% to 24%. Values for β (averaged per projection view) were found to be between 2.67 and 3.73. Thus, the range of textures of the simulated breasts covers the textures observed in clinical images.
CONCLUSIONS: Using these new techniques, digital anthropomorphic breast phantoms can be generated with a variety of glandular fractions and patterns. β values for this new phantom are comparable with published values for breast tissue in x-ray projection modalities. The combination of conspicuous linear structures and binarized power-law noise added to a limited area of the phantom qualitatively improves its realism.
© 2012 American Association of Physicists in Medicine.

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Year:  2012        PMID: 22755718      PMCID: PMC3371078          DOI: 10.1118/1.4718576

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  20 in total

1.  Optimized generation of high resolution breast anthropomorphic software phantoms.

Authors:  David D Pokrajac; Andrew D A Maidment; Predrag R Bakic
Journal:  Med Phys       Date:  2012-04       Impact factor: 4.071

2.  Task-based assessment of breast tomosynthesis: effect of acquisition parameters and quantum noise.

Authors:  I Reiser; R M Nishikawa
Journal:  Med Phys       Date:  2010-04       Impact factor: 4.071

3.  The myth of the 50-50 breast.

Authors:  M J Yaffe; J M Boone; N Packard; O Alonzo-Proulx; S Y Huang; C L Peressotti; A Al-Mayah; K Brock
Journal:  Med Phys       Date:  2009-12       Impact factor: 4.071

4.  Comparison of power spectra for tomosynthesis projections and reconstructed images.

Authors:  Emma Engstrom; Ingrid Reiser; Robert Nishikawa
Journal:  Med Phys       Date:  2009-05       Impact factor: 4.071

5.  The effect of skin thickness determined using breast CT on mammographic dosimetry.

Authors:  Shih-Ying Huang; John M Boone; Kai Yang; Alexander L C Kwan; Nathan J Packard
Journal:  Med Phys       Date:  2008-04       Impact factor: 4.071

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

Authors:  Christina M Li; W Paul Segars; Georgia D Tourassi; John M Boone; James T Dobbins
Journal:  Med Phys       Date:  2009-07       Impact factor: 4.071

7.  Development and characterization of an anthropomorphic breast software phantom based upon region-growing algorithm.

Authors:  Predrag R Bakic; Cuiping Zhang; Andrew D A Maidment
Journal:  Med Phys       Date:  2011-06       Impact factor: 4.071

8.  The characterization of breast anatomical metrics using dedicated breast CT.

Authors:  Shih-Ying Huang; John M Boone; Kai Yang; Nathan J Packard; Sarah E McKenney; Nicolas D Prionas; Karen K Lindfors; Martin J Yaffe
Journal:  Med Phys       Date:  2011-04       Impact factor: 4.071

9.  Human observer detection experiments with mammograms and power-law noise.

Authors:  A E Burgess; F L Jacobson; P F Judy
Journal:  Med Phys       Date:  2001-04       Impact factor: 4.071

10.  An anthropomorphic breast model for breast imaging simulation and optimization.

Authors:  Baiyu Chen; Jamie Shorey; Robert S Saunders; Samuel Richard; John Thompson; Loren W Nolte; Ehsan Samei
Journal:  Acad Radiol       Date:  2011-03-11       Impact factor: 3.173

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  12 in total

1.  Population of 224 realistic human subject-based computational breast phantoms.

Authors:  David W Erickson; Jered R Wells; Gregory M Sturgeon; Ehsan Samei; James T Dobbins; W Paul Segars; Joseph Y Lo
Journal:  Med Phys       Date:  2016-01       Impact factor: 4.071

Review 2.  Task-based measures of image quality and their relation to radiation dose and patient risk.

Authors:  Harrison H Barrett; Kyle J Myers; Christoph Hoeschen; Matthew A Kupinski; Mark P Little
Journal:  Phys Med Biol       Date:  2015-01-07       Impact factor: 3.609

3.  Objective models of compressed breast shapes undergoing mammography.

Authors:  Steve Si Jia Feng; Bhavika Patel; Ioannis Sechopoulos
Journal:  Med Phys       Date:  2013-03       Impact factor: 4.071

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

Authors:  Z Zhao; G J Gang; J H Siewerdsen
Journal:  Med Phys       Date:  2014-06       Impact factor: 4.071

5.  Development of realistic multi-contrast textured XCAT (MT-XCAT) phantoms using a dual-discriminator conditional-generative adversarial network (D-CGAN).

Authors:  Yushi Chang; Kyle Lafata; William Paul Segars; Fang-Fang Yin; Lei Ren
Journal:  Phys Med Biol       Date:  2020-03-19       Impact factor: 3.609

6.  Finite-element modeling of compression and gravity on a population of breast phantoms for multimodality imaging simulation.

Authors:  Gregory M Sturgeon; Nooshin Kiarashi; Joseph Y Lo; E Samei; W P Segars
Journal:  Med Phys       Date:  2016-05       Impact factor: 4.071

7.  Anatomically and physiologically informed computational model of hepatic contrast perfusion for virtual imaging trials.

Authors:  Thomas J Sauer; Ehsan Abadi; Paul Segars; Ehsan Samei
Journal:  Med Phys       Date:  2022-03-20       Impact factor: 4.506

8.  Synthetic breast phantoms from patient based eigenbreasts.

Authors:  Gregory M Sturgeon; Subok Park; William Paul Segars; Joseph Y Lo
Journal:  Med Phys       Date:  2017-10-19       Impact factor: 4.071

9.  Validation of a power-law noise model for simulating small-scale breast tissue.

Authors:  I Reiser; A Edwards; R M Nishikawa
Journal:  Phys Med Biol       Date:  2013-08-12       Impact factor: 3.609

10.  Generation of polychromatic projection for dedicated breast computed tomography simulation using anthropomorphic numerical phantom.

Authors:  Hosang Jeon; Hanbean Youn; Jin Sung Kim; Jiho Nam; Jayoung Lee; Juhye Lee; Dahl Park; Wontaek Kim; Yongkan Ki; Donghyun Kim
Journal:  PLoS One       Date:  2017-11-06       Impact factor: 3.240

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