Accelerated RAKI reconstruction for multi-slice cardiac cine applications.

ABSTRACT:

Background

Accelerated MRI reconstruction techniques are necessary to avoid long cardiac exams. K-space-based parallel imaging (PI) reconstruction has recently been adapted to deep learning with a scan-specific training technique entitled scan-specific robust artificial neural-networks for k-space interpolation (RAKI), which incorporates nonlinearity by applying convolutional neural networks. While the scan-specific aspect alleviates the need for a large training database, as it consists of a single-shot training, it consequently increases the overall reconstruction time.

Purpose

The aim of this study is to adapt RAKI reconstruction to cardiac cine acquisitions by optimizing the training strategy and exploiting the spatio-temporal redundancy while ensuring image quality.

SUBMITTER: Quillien L 

PROVIDER: S-EPMC12630071 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature