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Portrait of Predrag Bakic. Photo

Predrag Bakic

Associate Professor

Portrait of Predrag Bakic. Photo

Novel Perlin-based phantoms using 3D models of compressed breast shapes and fractal noise

Author

  • Joao P.V. Teixeira
  • Telmo M. Silva Filho
  • Thais G. Do Rego
  • Yuri B. Malheiros
  • Magnus Dustler
  • Predrag R. Bakic
  • Trevor L. Vent
  • Raymond J. Acciavatti
  • Srilalan Krishnamoorthy
  • Suleman Surti
  • Andrew D.A. Maidment
  • Bruno Barufaldi
Show all

Editor

  • Wei Zhao
  • Lifeng Yu

Summary, in English

Virtual clinical trials (VCTs) have been used widely to evaluate digital breast tomosynthesis (DBT) systems. VCTs require realistic simulations of the breast anatomy (phantoms) to characterize lesions and to estimate risk of masking cancers. This study introduces the use of Perlin-based phantoms to optimize the acquisition geometry of a novel DBT prototype. These phantoms were developed using a GPU implementation of a novel library called Perlin-CuPy. The breast anatomy is simulated using 3D models under mammography cranio-caudal compression. In total, 240 phantoms were created using compressed breast thickness, chest-wall to nipple distance, and skin thickness that varied in a {[35, 75], [59, 130), [1.0, 2.0]} mm interval, respectively. DBT projections and reconstructions of the phantoms were simulated using two acquisition geometries of our DBT prototype. The performance of both acquisition geometries was compared using breast volume segmentations of the Perlin phantoms. Results show that breast volume estimates are improved with the introduction of posterior-anterior motion of the x-ray source in DBT acquisitions. The breast volume is overestimated in DBT, varying substantially with the acquisition geometry; segmentation errors are more evident for thicker and larger breasts. These results provide additional evidence and suggest that custom acquisition geometries can improve the performance and accuracy in DBT. Perlin phantoms help to identify limitations in acquisition geometries and to optimize the performance of the DBT prototypes.

Department/s

  • Medical Radiation Physics, Malmö
  • Radiology Diagnostics, Malmö
  • LUCC: Lund University Cancer Centre

Publishing year

2022

Language

English

Publication/Series

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volume

12031

Document type

Conference paper

Publisher

SPIE

Topic

  • Radiology, Nuclear Medicine and Medical Imaging
  • Medical Image Processing

Keywords

  • digital breast tomosynthesis
  • Perlin noise
  • ray-tracing
  • virtual clinical trial

Conference name

Medical Imaging 2022: Physics of Medical Imaging

Conference date

2022-03-21 - 2022-03-27

Conference place

Virtual, Online

Status

Published

Research group

  • Medical Radiation Physics, Malmö
  • Radiology Diagnostics, Malmö

ISBN/ISSN/Other

  • ISSN: 1605-7422
  • ISBN: 9781510649378