In this study, we examine the performance of the simultaneous algebraic reconstruction technique (SART) for
digital breast tomosynthesis under variations in key imaging parameters, such as the number of iterations,
number of projections, angular range, initial guess, radiation dose, etc. We use a real breast CT volume as a
ground truth digital phantom from which to simulate x-ray projections under the various selected conditions.
The reconstructed image quality is measured using task-based metrics, namely signal CNR and the AUC of a
Channelised Hotelling Observer with Laguerre-Gauss basis functions. The task at hand is a signal-known-exactly
(SKE) task, where the objective is to detect a simulated mass inserted into the breast CT volume.
We present a novel method for the detection and reconstruction in 3D of microcalcifications in digital breast
tomosynthesis (DBT) image sets. From a list of microcalcification candidate regions (that is, real microcalcification
points or noise points) found in each DBT projection, our method: (1) finds the set of corresponding points of a
microcalcification in all the other projections; (2) locates its 3D position in the breast; (3) highlights noise points; and (4)
identifies the failure of microcalcification detection in one or more projections, in which case the method predicts the
image locations of the microcalcification in the images in which they are missed.
From the geometry of the DBT acquisition system, an "epipolar curve" is derived for the 2D positions a
microcalcification in each projection generated at different angular positions. Each epipolar curve represents a single
microcalcification point in the breast. By examining the n projections of m microcalcifications in DBT, one expects
ideally m epipolar curves each comprising n points. Since each microcalcification point is at a different 3D position,
each epipolar curve will be at a different position in the same 2D coordinate system. By plotting all the
microcalcification candidates in the same 2D plane simultaneously, one can easily extract a representation of the number
of microcalcification points in the breast (number of epipolar curves) and their 3D positions, the noise points detected
(isolated points not forming any epipolar curve) and microcalcification points missed in some projections (epipolar
curves with less than n points).