Comparison of data-driven and general temporal constraints on compressed sensing for breast DCE MRI.

ABSTRACT:

Purpose

Current breast DCE-MRI strategies provide high sensitivity for cancer detection but are known to be insufficient in fully capturing rapidly changing contrast kinetics at high spatial resolution across both breasts. Advanced acquisition and reconstruction strategies aim to improve spatial and temporal resolution and increase specificity for disease characterization. In this work, we evaluate the spatial and temporal fidelity of a modified data-driven low-rank-based model (known as MOCCO, model consistency condition) compressed-sensing (CS) reconstruction compared to CS with temporal total variation with radial acquisition for high spatial-temporal breast DCE MRI.

Methods

Reconstruction performance was characterized using numerical simulations of a golden-angle stack-o

SUBMITTER: Wang PN 

PROVIDER: S-EPMC11542549 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature