TY - GEN
T1 - Modeling human-perceived quality for the assessment of digitized histopathology color standardization
AU - Mosquera-Lopez, Clara
AU - Escobar, Rodrigo
AU - Agaian, Sos
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/10/7
Y1 - 2015/10/7
N2 - Color consistency is still one of the most significant problems in whole-slide imaging since even subtle variations of color appearance in digitized slides might cause image misinterpretation by pathologists or by computer-aided diagnosis systems. These variations are mainly caused by differences in laboratory protocols and imaging devices manufactures. In this paper we propose a model for assessing color standardization algorithms in whole-slide histopathology imaging based on two metrics: (i) the color similarity between a template well-stained image and the resulting color-standardized image, and (ii) the structural distortion caused by the application of a color standardization algorithm. We employed the χ2 histogram distance as color distance measure, and the Universal Quality (Q) index for quantifying structural distortion. The developed model produce an overall quality score (OQS) in the range [0, 10] that correlates well with human-perceived color standardization quality. To the best of our knowledge, this is the first attempt to measure the efficacy of color standardization algorithms in digital pathology.
AB - Color consistency is still one of the most significant problems in whole-slide imaging since even subtle variations of color appearance in digitized slides might cause image misinterpretation by pathologists or by computer-aided diagnosis systems. These variations are mainly caused by differences in laboratory protocols and imaging devices manufactures. In this paper we propose a model for assessing color standardization algorithms in whole-slide histopathology imaging based on two metrics: (i) the color similarity between a template well-stained image and the resulting color-standardized image, and (ii) the structural distortion caused by the application of a color standardization algorithm. We employed the χ2 histogram distance as color distance measure, and the Universal Quality (Q) index for quantifying structural distortion. The developed model produce an overall quality score (OQS) in the range [0, 10] that correlates well with human-perceived color standardization quality. To the best of our knowledge, this is the first attempt to measure the efficacy of color standardization algorithms in digital pathology.
KW - Color standardization quality
KW - computer-aided diagnosis (CAD)
KW - digital pathology
KW - histopathology image analysis
KW - whole-slide imaging
UR - http://www.scopus.com/inward/record.url?scp=84962758505&partnerID=8YFLogxK
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U2 - 10.1109/IST.2015.7294526
DO - 10.1109/IST.2015.7294526
M3 - Conference contribution
AN - SCOPUS:84962758505
T3 - IST 2015 - 2015 IEEE International Conference on Imaging Systems and Techniques, Proceedings
BT - IST 2015 - 2015 IEEE International Conference on Imaging Systems and Techniques, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th IEEE International Conference on Imaging Systems and Techniques, IST 2015
Y2 - 16 September 2015 through 18 September 2015
ER -