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

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

doi:10.1117/12.2612565

4 April 2022 Novel Perlin-based phantoms using 3D models of compressed breast shapes and fractal noise

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

Author Affiliations +

Proceedings Volume 12031, Medical Imaging 2022: Physics of Medical Imaging; 120313S (2022) https://doi.org/10.1117/12.2612565
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Conference Poster

Abstract

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.

Conference Presentation

Citation Download Citation

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, and Bruno Barufaldi "Novel Perlin-based phantoms using 3D models of compressed breast shapes and fractal noise", Proc. SPIE 12031, Medical Imaging 2022: Physics of Medical Imaging, 120313S (4 April 2022); https://doi.org/10.1117/12.2612565

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available