TY - JOUR
T1 - Validation of a mammographic image quality modification algorithm using 3D-printed breast phantoms
AU - Boita, Joana
AU - MacKenzie, Alistair
AU - Van Engen, Ruben E.
AU - Broeders, Mireille
AU - Sechopoulos, Ioannis
N1 - Funding Information:
The authors thank the Jarvis Breast Screening Unit in Guildford and the Foundation of Population Screening East, in Nijmegen, for access to their mammography systems; Christian Fedon and the physics team from the Dutch Expert Centre for Screening (LRCB), in Nijmegen, for helping with the measurements; and, finally, Stephan Schopphoven and Ulf Mäder for providing information about the behavior and characteristics of the breast phantoms. The author Alistair Mackenzie was funded as part of the OPTIMAM2 project and is supported by Cancer Research UK (Grant No. C30682/A17321). This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Publisher Copyright:
© 2021 Society of Photo-Optical Instrumentation Engineers (SPIE).
PY - 2021/5/20
Y1 - 2021/5/20
N2 - Purpose: To validate a previously proposed algorithm that modifies a mammogram to appear as if it was acquired with different technique factors using realistic phantom-based mammograms. Approach: Two digital mammography systems (an indirect-and a direct-detector-based system) were used to acquire realistic mammographic images of five 3D-printed breast phantoms with the technique factors selected by the automatic exposure control and at various other conditions (denoted by the original images). Additional images under other simulated conditions were also acquired: higher or lower tube voltages, different anode/filter combinations, or lower tube current-time products (target images). The signal and noise in the original images were modified to simulate the target images (simulated images). The accuracy of the image modification algorithm was validated by comparing the target and simulated images using the local mean, local standard deviation (SD), local variance, and power spectra (PS) of the image signals. The absolute relative percent error between the target and simulated images for each parameter was calculated at each sub-region of interest (local parameters) and frequency (PS), and then averaged. Results: The local mean signal, local SD, local variance, and PS of the target and simulated images were very similar, with a relative percent error of 5.5%, 3.8%, 7.8%, and 4.4% (indirect system), respectively, and of 3.7%, 3.8%, 7.7%, and 7.5% (direct system), respectively. Conclusions: The algorithm is appropriate for simulating different technique factors. Therefore, it can be used in various studies, for instance to evaluate the impact of technique factors in cancer detection using clinical images.
AB - Purpose: To validate a previously proposed algorithm that modifies a mammogram to appear as if it was acquired with different technique factors using realistic phantom-based mammograms. Approach: Two digital mammography systems (an indirect-and a direct-detector-based system) were used to acquire realistic mammographic images of five 3D-printed breast phantoms with the technique factors selected by the automatic exposure control and at various other conditions (denoted by the original images). Additional images under other simulated conditions were also acquired: higher or lower tube voltages, different anode/filter combinations, or lower tube current-time products (target images). The signal and noise in the original images were modified to simulate the target images (simulated images). The accuracy of the image modification algorithm was validated by comparing the target and simulated images using the local mean, local standard deviation (SD), local variance, and power spectra (PS) of the image signals. The absolute relative percent error between the target and simulated images for each parameter was calculated at each sub-region of interest (local parameters) and frequency (PS), and then averaged. Results: The local mean signal, local SD, local variance, and PS of the target and simulated images were very similar, with a relative percent error of 5.5%, 3.8%, 7.8%, and 4.4% (indirect system), respectively, and of 3.7%, 3.8%, 7.7%, and 7.5% (direct system), respectively. Conclusions: The algorithm is appropriate for simulating different technique factors. Therefore, it can be used in various studies, for instance to evaluate the impact of technique factors in cancer detection using clinical images.
KW - digital mammography
KW - image quality
KW - image simulation
KW - virtual clinical trials
UR - http://www.scopus.com/inward/record.url?scp=85108991586&partnerID=8YFLogxK
U2 - 10.1117/1.JMI.8.3.033502
DO - 10.1117/1.JMI.8.3.033502
M3 - Article
AN - SCOPUS:85108991586
SN - 2329-4302
VL - 8
JO - Journal of medical imaging
JF - Journal of medical imaging
IS - 3
M1 - 033502
ER -