Use of a Total Variation Minimization Iterative Reconstruction Algorithm to Evaluate Reduced Projections during Digital Breast Tomosynthesis

Abstract EN

Purpose.

We evaluated the efficacies of the adaptive steepest descent projection onto convex sets (ASD-POCS), simultaneous algebraic reconstruction technique (SART), filtered back projection (FBP), and maximum likelihood expectation maximization (MLEM) total variation minimization iterative algorithms for reducing exposure doses during digital breast tomosynthesis for reduced projections.

Methods.

Reconstructions were evaluated using normal (15 projections) and half (i.e., thinned-out normal) projections (seven projections).

The algorithms were assessed by determining the full width at half-maximum (FWHM), and the BR3D Phantom was used to evaluate the contrast-to-noise ratio (CNR) for the in-focus plane.

A mean similarity measure of structural similarity (MSSIM) was also used to identify the preservation of contrast in clinical cases.

Results.

Spatial resolution tended to deteriorate in ASD-POCS algorithm reconstructions involving a reduced number of projections.

However, the microcalcification size did not affect the rate of FWHM change.

The ASD-POCS algorithm yielded a high CNR independently of the simulated mass lesion size and projection number.

The ASD-POCS algorithm yielded a high MSSIM in reconstructions from reduced numbers of projections.

Conclusions.

The ASD-POCS algorithm can preserve contrast despite a reduced number of projections and could therefore be used to reduce radiation doses.