Using automated texture features to determine the probability for masking of a tumor on mammography, but not ultrasound

Using automated texture features to determine the probability for masking of a tumor on mammography, but not ultrasound

Abstract Background Tumors in radiologically dense breast were overlooked on mammograms more often than tumors in low-density breasts. A fast reproducible and automated method of assessing percentage mammographic density (PMD) would be desirable to support decisions whether ultrasonography should be...

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Bibliographic Details
Main Authors: Lothar Häberle, Carolin C.  Hack, Katharina Heusinger, Florian Wagner, Sebastian M. Jud, Michael Uder, Matthias W.  Beckmann, Rüdiger Schulz-Wendtland, Thomas Wittenberg, Peter A.  Fasching
Format: Article
Language:English
Published: BMC 2017-08-01
Series:European Journal of Medical Research
Subjects:
Mammography screening
Texture analysis
Masking
Mammographic density
Sensitivity
Risk prediction
Online Access:http://link.springer.com/article/10.1186/s40001-017-0270-0

Internet

http://link.springer.com/article/10.1186/s40001-017-0270-0

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