Title: Investigating Simulation-Based Metrics for Characterizing Linear Iterative Reconstruction in Digital Breast Tomosynthesis,
Abstract: Simulation-based image quality metrics are adapted and investigated for
characterizing the parameter dependences of linear iterative image
reconstruction for DBT. Three metrics based on 2D DBT simulation are
investigated: (1) a root-mean-square-error (RMSE) between the test phantom and
reconstructed image, (2) a gradient RMSE where the comparison is made after
taking a spatial gradient of both image and phantom, and (3) a
region-of-interest (ROI) Hotelling observer (HO) for
signal-known-exactly/background-known-exactly (SKE/BKE) and
signal-known-exactly/background-known-statistically (SKE/BKS) detection tasks.
Two simulation studies are performed using the aforementioned metrics, varying
voxel aspect ratio and regularization strength for two types of Tikhonov
regularized least-squares optimization. The RMSE metrics are applied to a 2D
test phantom and the ROI-HO metric is applied to two tasks relevant to DBT:
large, low contrast lesion detection and small, high contrast
microcalcification detection. The RMSE metric trends are compared with visual
assessment of the reconstructed test phantom. The ROI-HO metric trends are
compared with 3D reconstructed images from ACR phantom data acquired with a
Hologic Selenia Dimensions DBT system. Sensitivity of image RMSE to mean pixel
value is found to limit its applicability to the assessment of DBT image
reconstruction. Image gradient RMSE is insensitive to mean pixel value and
appears to track better with subjective visualization of the reconstructed
bar-pattern phantom. The ROI-HO metric shows an increasing trend with
regularization strength for both forms of Tikhonov-regularized least-squares;
however, this metric saturates at intermediate regularization strength
indicating a point of diminishing returns for signal detection. Visualization
with reconstructed ACR phantom images appears to show a similar dependence with
regularization strength.