ArticleMedical physics2016
Population of 224 realistic human subject-based computational breast phantoms.
Article in Medical physics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Article
- Examining the influence of digital phantom models in virtual imaging trials for tomographic breast imaging.Journal of medical imaging (Bellingham, Wash.) · 2025Article
- Assessment of scatter radiation dose received by comforters and carers during digital breast tomosynthesis mammography.Journal of medical radiation sciences · 2023Article
- Noninvasive Electrical Stimulation Neuromodulation and Digital Brain Technology: A Review.Biomedicines · 2023Review
- An Anthropomorphic Digital Reference Object (DRO) for Simulation and Analysis of Breast DCE MRI Techniques.Tomography (Ann Arbor, Mich.) · 2022Article
- Impact of Using Uniform Attenuation Coefficients for Heterogeneously Dense Breasts in a Dedicated Breast PET/X-ray Scanner.IEEE transactions on radiation and plasma medical sciences · 2020Article
- Virtual clinical trials in medical imaging: a review.Journal of medical imaging (Bellingham, Wash.) · 2020Review
- DukeSim: A Realistic, Rapid, and Scanner-Specific Simulation Framework in Computed Tomography.IEEE transactions on medical imaging · 2019Article
- Three-dimensionally-printed anthropomorphic physical phantom for mammography and digital breast tomosynthesis with custom materials, lesions, and uniform quality control region.Journal of medical imaging (Bellingham, Wash.) · 2019Article
- Toward 7T breast MRI clinical study: safety assessment using simulation of heterogeneous breast models in RF exposure.Magnetic resonance in medicine · 2019Article
- Learning-based stochastic object models for characterizing anatomical variations.Physics in medicine and biology · 2018Article
- Virtual assessment of stereoscopic viewing of digital breast tomosynthesis projection images.Journal of medical imaging (Bellingham, Wash.) · 2018Article
- Synthetic breast phantoms from patient based eigenbreasts.Medical physics · 2017Article
- Anthropomorphic dual-lattice voxel models for optimizing image quality and dose.Journal of medical imaging (Bellingham, Wash.) · 2017Article
- Virtual Human Models for Electromagnetic Studies and Their Applications.IEEE reviews in biomedical engineering · 2017Review
- Accuracy assessment and characterization of x-ray coded aperture coherent scatter spectral imaging for breast cancer classification.Journal of medical imaging (Bellingham, Wash.) · 2017Article
- Impact of breast structure on lesion detection in breast tomosynthesis, a simulation study.Journal of medical imaging (Bellingham, Wash.) · 2016Article
- Review
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7 authors.
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Abstract
purposeTo create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data.
methodsA tissue classification and segmentation algorithm was used to create realistic and detailed 3D computational breast phantoms based on 230 + dedicated bCT datasets from normal human subjects. The breast volume was identified using a coarse three-class fuzzy C-means segmentation algorithm which accounted for and removed motion blur at the breast periphery. Noise in the bCT data was reduced through application of a postreconstruction 3D bilateral filter. A 3D adipose nonuniformity (bias field) correction was then applied followed by glandular segmentation using a 3D bias-corrected fuzzy C-means algorithm. Multiple tissue classes were defined including skin, adipose, and several fractional glandular densities. Following segmentation, a skin mask was produced which preserved the interdigitated skin, adipose, and glandular boundaries of the skin interior. Finally, surface modeling was used to produce digital phantoms with methods complementary to the XCAT suite of digital human phantoms.
resultsAfter rejecting some datasets due to artifacts, 224 virtual breast phantoms were created which emulate the complex breast parenchyma of actual human subjects. The volume breast density (with skin) ranged from 5.5% to 66.3% with a mean value of 25.3% ± 13.2%. Breast volumes ranged from 25.0 to 2099.6 ml with a mean value of 716.3 ± 386.5 ml. Three breast phantoms were selected for imaging with digital compression (using finite element modeling) and simple ray-tracing, and the results show promise in their potential to produce realistic simulated mammograms.
conclusionsThis work provides a new population of 224 breast phantoms based on in vivo bCT data for imaging research. Compared to previous studies based on only a few prototype cases, this dataset provides a rich source of new cases spanning a wide range of breast types, volumes, densities, and parenchymal patterns.
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