TY - GEN
T1 - Validation of the textural realism of a 3D anthropomorphic phantom for digital breast tomosynthesis
AU - Acciavatti, Raymond J.
AU - Hsieh, Meng Kang
AU - Gastounioti, Aimilia
AU - Hu, Yifan
AU - Chen, Jinbo
AU - Maidment, Andrew D.A.
AU - Kontos, Despina
N1 - Publisher Copyright:
© 2018 SPIE.
PY - 2018
Y1 - 2018
N2 - In this paper, texture calculations are used to validate the realism of a physical anthropomorphic phantom for digital breast tomosynthesis. The texture features were compared against clinical mammography data. Three groups of features (grey-level histogram, co-occurrence, and run-length) were considered. The features were analyzed over a broad range of technique settings (kV and mAs). These calculations were done in the central slice of the reconstruction as well as the synthetic 2D mammogram. For each feature, the clinical data were binned into strata based on the compressed breast thickness. It was demonstrated that the clinical features vary by thickness. To evaluate the realism of the phantom, each feature was compared against clinical data in the same thickness stratum. For the purpose of this paper, a feature was considered to be realistic if it was within the middle 95% of the statistical distribution of clinical values. In the reconstruction, most features were found to exhibit realism; specifically, all 12 grey-level histogram features, four out of seven co-occurrence features, and three out of seven run-length features. The realism of most features was robust to changes in the technique settings. However, in the synthetic 2D mammogram, fewer features were found to exhibit realism. In conclusion, this paper provides a validation of the textural realism of the phantom in the reconstruction, and shows that there is less realism in the synthetic 2D mammogram. We identify the features that should be considered to refine the design of the phantom in future work.
AB - In this paper, texture calculations are used to validate the realism of a physical anthropomorphic phantom for digital breast tomosynthesis. The texture features were compared against clinical mammography data. Three groups of features (grey-level histogram, co-occurrence, and run-length) were considered. The features were analyzed over a broad range of technique settings (kV and mAs). These calculations were done in the central slice of the reconstruction as well as the synthetic 2D mammogram. For each feature, the clinical data were binned into strata based on the compressed breast thickness. It was demonstrated that the clinical features vary by thickness. To evaluate the realism of the phantom, each feature was compared against clinical data in the same thickness stratum. For the purpose of this paper, a feature was considered to be realistic if it was within the middle 95% of the statistical distribution of clinical values. In the reconstruction, most features were found to exhibit realism; specifically, all 12 grey-level histogram features, four out of seven co-occurrence features, and three out of seven run-length features. The realism of most features was robust to changes in the technique settings. However, in the synthetic 2D mammogram, fewer features were found to exhibit realism. In conclusion, this paper provides a validation of the textural realism of the phantom in the reconstruction, and shows that there is less realism in the synthetic 2D mammogram. We identify the features that should be considered to refine the design of the phantom in future work.
KW - Anthropomorphic Phantom
KW - Digital Breast Tomosynthesis
KW - Image Acquisition
KW - Image Reconstruction
KW - Synthetic 2D Mammogram
KW - Texture Feature Analysis
UR - http://www.scopus.com/inward/record.url?scp=85050180581&partnerID=8YFLogxK
U2 - 10.1117/12.2318029
DO - 10.1117/12.2318029
M3 - Conference contribution
AN - SCOPUS:85050180581
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - 14th International Workshop on Breast Imaging (IWBI 2018)
A2 - Krupinski, Elizabeth A.
PB - SPIE
T2 - 14th International Workshop on Breast Imaging (IWBI 2018)
Y2 - 8 July 2018 through 11 July 2018
ER -