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Representation of Complex Mammary Parenchyma Texture in Tomosynthesis Using Simplex Noise Simulations

Barufaldi, Bruno ; Choi, Chloe J. ; Teixeira, Joao P.V. ; Dustler, Magnus LU orcid ; Englander, Raphael B. ; do Rêgo, Thaís G. ; Malheiros, Yuri ; Silva Filho, Telmo M. ; Hossain, Belayat and Lee, Juhun , et al. (2024) Medical Imaging 2024: Physics of Medical Imaging In Progress in Biomedical Optics and Imaging - Proceedings of SPIE 12925.
Abstract

The mammary parenchyma is a complex arrangement of tissues that can greatly vary among individuals, potentially masking cancers in breast screening images. In this work, we propose a Simplex-based method to simulate anatomical patterns and textures seen in digital breast tomosynthesis. Our approach involves selecting appropriate Simplex noise parameters to represent distinct categories of breast parenchyma with variable volumetric breast density (%VBD). We use volumetric coarse masks (70 × 60 × 50 mm3) to outline patches of both dense and adipose tissues. These masks serve as a foundation for volumetric and multi-scale Simplex-based noise distributions. The Simplex-based noise distributions are normalized and thresholded... (More)

The mammary parenchyma is a complex arrangement of tissues that can greatly vary among individuals, potentially masking cancers in breast screening images. In this work, we propose a Simplex-based method to simulate anatomical patterns and textures seen in digital breast tomosynthesis. Our approach involves selecting appropriate Simplex noise parameters to represent distinct categories of breast parenchyma with variable volumetric breast density (%VBD). We use volumetric coarse masks (70 × 60 × 50 mm3) to outline patches of both dense and adipose tissues. These masks serve as a foundation for volumetric and multi-scale Simplex-based noise distributions. The Simplex-based noise distributions are normalized and thresholded using gradient level sets selected to binarize specific Simplex frequencies. The Simplex frequencies are summed and binarized using post-hoc thresholds, resulting in patches of tissue tailored to represent anatomic-like structures seen in digital breast tomosynthesis (DBT) images. We simulate DBT projections and reconstructions of the patches of breast tissue following the acquisition geometry and exposure settings of a clinical tomosynthesis system. We calculate the power spectra and estimate the power-law exponent (β) using a sample of DBT reconstructions (n=500, equally stratified by four density classes). Our findings reveal an absolute β value of 3.0, indicative of the improvements achieved in both the performance and realism of the breast tissue simulation. In summary, our proposed Simplex-based method enhances realism and texture variations, ensuring the presence of anatomical and quantum noise at levels consistent with the image quality expected in breast screening exams.

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organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
anthropomorphic phantoms, breast cancer risk assessment, breast complexity, Perlin noise, Simplex noise
host publication
Medical Imaging 2024 : Physics of Medical Imaging - Physics of Medical Imaging
series title
Progress in Biomedical Optics and Imaging - Proceedings of SPIE
editor
Fahrig, Rebecca ; Sabol, John M. and Li, Ke
volume
12925
article number
1292548
publisher
SPIE
conference name
Medical Imaging 2024: Physics of Medical Imaging
conference location
San Diego, United States
conference dates
2024-02-19 - 2024-02-22
external identifiers
  • scopus:85191443975
ISSN
1605-7422
ISBN
9781510671546
DOI
10.1117/12.3006839
language
English
LU publication?
yes
id
1c53ffa9-7822-41f8-8713-9735392e2c89
date added to LUP
2025-01-15 14:06:29
date last changed
2025-04-04 14:50:05
@inproceedings{1c53ffa9-7822-41f8-8713-9735392e2c89,
  abstract     = {{<p>The mammary parenchyma is a complex arrangement of tissues that can greatly vary among individuals, potentially masking cancers in breast screening images. In this work, we propose a Simplex-based method to simulate anatomical patterns and textures seen in digital breast tomosynthesis. Our approach involves selecting appropriate Simplex noise parameters to represent distinct categories of breast parenchyma with variable volumetric breast density (%VBD). We use volumetric coarse masks (70 × 60 × 50 mm<sup>3</sup>) to outline patches of both dense and adipose tissues. These masks serve as a foundation for volumetric and multi-scale Simplex-based noise distributions. The Simplex-based noise distributions are normalized and thresholded using gradient level sets selected to binarize specific Simplex frequencies. The Simplex frequencies are summed and binarized using post-hoc thresholds, resulting in patches of tissue tailored to represent anatomic-like structures seen in digital breast tomosynthesis (DBT) images. We simulate DBT projections and reconstructions of the patches of breast tissue following the acquisition geometry and exposure settings of a clinical tomosynthesis system. We calculate the power spectra and estimate the power-law exponent (β) using a sample of DBT reconstructions (n=500, equally stratified by four density classes). Our findings reveal an absolute β value of 3.0, indicative of the improvements achieved in both the performance and realism of the breast tissue simulation. In summary, our proposed Simplex-based method enhances realism and texture variations, ensuring the presence of anatomical and quantum noise at levels consistent with the image quality expected in breast screening exams.</p>}},
  author       = {{Barufaldi, Bruno and Choi, Chloe J. and Teixeira, Joao P.V. and Dustler, Magnus and Englander, Raphael B. and do Rêgo, Thaís G. and Malheiros, Yuri and Silva Filho, Telmo M. and Hossain, Belayat and Lee, Juhun and Maidment, Andrew D.A.}},
  booktitle    = {{Medical Imaging 2024 : Physics of Medical Imaging}},
  editor       = {{Fahrig, Rebecca and Sabol, John M. and Li, Ke}},
  isbn         = {{9781510671546}},
  issn         = {{1605-7422}},
  keywords     = {{anthropomorphic phantoms; breast cancer risk assessment; breast complexity; Perlin noise; Simplex noise}},
  language     = {{eng}},
  publisher    = {{SPIE}},
  series       = {{Progress in Biomedical Optics and Imaging - Proceedings of SPIE}},
  title        = {{Representation of Complex Mammary Parenchyma Texture in Tomosynthesis Using Simplex Noise Simulations}},
  url          = {{http://dx.doi.org/10.1117/12.3006839}},
  doi          = {{10.1117/12.3006839}},
  volume       = {{12925}},
  year         = {{2024}},
}