University of Illinois Urbana-Champaign

Three-dimensional, in-silico breast phantom for multimodality image simulations

Mahr, David M.

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Mahr_David.pdf

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https://hdl.handle.net/2142/14633

Description

Title
Three-dimensional, in-silico breast phantom for multimodality image simulations
Author(s)
Mahr, David M.
Issue Date
2010-01-06T16:20:10Z
Director of Research (if dissertation) or Advisor (if thesis)
Insana, Michael F.
Department of Study
Bioengineering
Discipline
Bioengineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2010-01-06T16:20:10Z
Keyword(s)
  • Breast imaging
  • Multimodality
  • Phantom
  • Anthropomorphic
  • Modeling
  • Mammography simulation
  • Ultrasound
  • Computed tomography
Abstract
We report on the construction of anatomically realistic three-dimensional in-silico breast phantoms with adjustable sizes, shapes and morphologic features. The concept of multiscale spatial resolution is implemented for generating breast tissue images from multiple modalities. Breast epidermal boundary and subcutaneous fat layer is generated by fitting an ellipsoid and 2nd degree polynomials to reconstructive surgical data and ultrasound imaging data. Intraglandular fat is simulated by randomly distributing and orienting adipose ellipsoids within a fibrous region immediately within the dermal layer. Cooper’s ligaments are simulated as fibrous ellipsoidal shells distributed within the subcutaneous fat layer. Individual ductal lobes are simulated following a random binary tree model which is generated based upon probabilistic branching conditions described by ramification matrices, as originally proposed by Bakic et al [3, 4]. The complete ductal structure of the breast is simulated from multiple lobes that extend from the base of the nipple and branch towards the chest wall. As lobe branching progresses, branches are reduced in height and radius and terminal branches are capped with spherical lobular clusters. Biophysical parameters are mapped onto the complete anatomical model and synthetic multimodal images (Mammography, Ultrasound, CT) are generated for phantoms of different adipose percentages (40%, 50%, 60%, and 70%) and are analytically compared with clinical examples. Results demonstrate that the in-silico breast phantom has applications in imaging performance evaluation and, specifically, great utility for solving image registration issues in multimodality imaging.
Graduation Semester
2009-12
Permalink
http://hdl.handle.net/2142/14633
Copyright and License Information
Copyright 2009 David Michael Mahr

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