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VOLUMETRIC LOCALISATION OF DENSE BREAST TISSUE USING BREAST TOMOSYNTHESIS DATA.

Dustler, Magnus LU orcid ; Petersson, Hannie LU and Timberg, Pontus LU (2016) In Radiation Protection Dosimetry
Abstract
This study attempted to use combined data from reconstructed digital breast tomosynthesis (DBT) volumes and density estimation of projection images to localise dense tissue inside the breast, using the assumption that the breast can be treated as consisting of only two types of tissue: fibroglandular (dense) and adipose (fatty). To be able to verify results, software breast phantoms generated using fractal Perlin noise were employed. Projection images were created using the PENELOPE Monte Carlo package. Dense tissue volume was estimated from the central projection image. The density image was used to determine the number of dense voxels at each pixel location, which were then placed using the DBT image as a template. The method proved... (More)
This study attempted to use combined data from reconstructed digital breast tomosynthesis (DBT) volumes and density estimation of projection images to localise dense tissue inside the breast, using the assumption that the breast can be treated as consisting of only two types of tissue: fibroglandular (dense) and adipose (fatty). To be able to verify results, software breast phantoms generated using fractal Perlin noise were employed. Projection images were created using the PENELOPE Monte Carlo package. Dense tissue volume was estimated from the central projection image. The density image was used to determine the number of dense voxels at each pixel location, which were then placed using the DBT image as a template. The method proved capable of accurately determining the composition of 75±5 % of voxels. (Less)
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author
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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Radiation Protection Dosimetry
publisher
Oxford University Press
external identifiers
  • pmid:26922782
  • pmid:26922782
  • scopus:84979080338
  • wos:000383492100062
ISSN
1742-3406
DOI
10.1093/rpd/ncw022
language
English
LU publication?
yes
id
5fdf5f6c-f91d-4be4-ac47-eb3eebf9facf (old id 8821408)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/26922782?dopt=Abstract
date added to LUP
2016-04-04 09:43:54
date last changed
2024-10-13 05:42:36
@article{5fdf5f6c-f91d-4be4-ac47-eb3eebf9facf,
  abstract     = {{This study attempted to use combined data from reconstructed digital breast tomosynthesis (DBT) volumes and density estimation of projection images to localise dense tissue inside the breast, using the assumption that the breast can be treated as consisting of only two types of tissue: fibroglandular (dense) and adipose (fatty). To be able to verify results, software breast phantoms generated using fractal Perlin noise were employed. Projection images were created using the PENELOPE Monte Carlo package. Dense tissue volume was estimated from the central projection image. The density image was used to determine the number of dense voxels at each pixel location, which were then placed using the DBT image as a template. The method proved capable of accurately determining the composition of 75±5 % of voxels.}},
  author       = {{Dustler, Magnus and Petersson, Hannie and Timberg, Pontus}},
  issn         = {{1742-3406}},
  language     = {{eng}},
  month        = {{02}},
  publisher    = {{Oxford University Press}},
  series       = {{Radiation Protection Dosimetry}},
  title        = {{VOLUMETRIC LOCALISATION OF DENSE BREAST TISSUE USING BREAST TOMOSYNTHESIS DATA.}},
  url          = {{http://dx.doi.org/10.1093/rpd/ncw022}},
  doi          = {{10.1093/rpd/ncw022}},
  year         = {{2016}},
}