Presentation + Paper
9 March 2018 Investigating the contributions of anatomical variations and quantum noise to image texture in digital breast tomosynthesis
Author Affiliations +
Abstract
Our previous work on DBT image texture indicates that certain texture features may impact human observer performance for the task of low-contrast mass detection. Despite this, little is yet known about these texture statistics in the context of medical imaging. In this study, we investigate the factors that influence texture features in simulated DBT images. Specifically, we explore whether or not changes in quantum noise and anatomical variations are reflected in image texture curves. Our findings concerning the effects of Wiener filtration and changes in DBT system parameters indicate that texture statistics are affected by both anatomical variations and quantum noise.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
William H. Nisbett, Amar Kavuri, and Mini Das "Investigating the contributions of anatomical variations and quantum noise to image texture in digital breast tomosynthesis", Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 105730H (9 March 2018); https://doi.org/10.1117/12.2294981
Lens.org Logo
CITATIONS
Cited by 2 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Digital breast tomosynthesis

Breast

Image filtering

Medical imaging

Image analysis

Image quality

Tumor growth modeling

Back to Top