TY - GEN
T1 - Natural Scene Statistics of Mammography Accreditation Phantom Images
AU - Guzmán, Valentina Corchuelo
AU - Darío Benítez Restrepo, Hernan
AU - Hurtado, Edison Salazar
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - Image quality assessment (IQA) protocol ensures that mammography equipment operates according to its design standards. IQA permits to detect alterations in the equipment that may impact negatively the interpretation of mammograms. The mammography accreditation phantom simulates the radio-graphic attenuation of an average-size compressed breast and contains structures that model very basic image characteristics of breast parenchyma and cancer. It is composed of a poly-methyl-methacrylate (PMMA) block 4.5 mm thick and a wax insert. The wax insert contains six disks, fibers, and calcifications. To pass the image quality standards for screen mammography, at least four fibers, three calcification groups, and three masses must be clearly visible by a human reader (with no obvious artifacts) at an average glandular dose of less than 2.5 mGy. Predicting human performance in quality control process is critical for task efficacy. In this paper, as a first step to predict automatically human performance in the recognition of structures, we analyze under different acquisition conditions the signal-to-noise ratio (SNR), the contrast-to-noise ratio (CNR) for the different types of structures present in a phantom MG image (PMGI) and the extraction of Natural Scene Statistics (NSS) from a PMGI.
AB - Image quality assessment (IQA) protocol ensures that mammography equipment operates according to its design standards. IQA permits to detect alterations in the equipment that may impact negatively the interpretation of mammograms. The mammography accreditation phantom simulates the radio-graphic attenuation of an average-size compressed breast and contains structures that model very basic image characteristics of breast parenchyma and cancer. It is composed of a poly-methyl-methacrylate (PMMA) block 4.5 mm thick and a wax insert. The wax insert contains six disks, fibers, and calcifications. To pass the image quality standards for screen mammography, at least four fibers, three calcification groups, and three masses must be clearly visible by a human reader (with no obvious artifacts) at an average glandular dose of less than 2.5 mGy. Predicting human performance in quality control process is critical for task efficacy. In this paper, as a first step to predict automatically human performance in the recognition of structures, we analyze under different acquisition conditions the signal-to-noise ratio (SNR), the contrast-to-noise ratio (CNR) for the different types of structures present in a phantom MG image (PMGI) and the extraction of Natural Scene Statistics (NSS) from a PMGI.
KW - Mammography
KW - Medical image
KW - Phantom
KW - Statistics
KW - quality assessment
UR - http://www.scopus.com/inward/record.url?scp=85068096403&partnerID=8YFLogxK
U2 - 10.1109/STSIVA.2019.8730289
DO - 10.1109/STSIVA.2019.8730289
M3 - Conference contribution
AN - SCOPUS:85068096403
T3 - 2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings
BT - 2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019
Y2 - 24 April 2019 through 26 April 2019
ER -
