Investigating the contributions of anatomical variations and quantum noise to image texture in digital breast tomosynthesis

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.

Duke Scholars

Author Amareswararao Kavuri