no code implementations • 18 May 2023 • Hengfa Lu, Huihui Ye, Lawrence L. Wald, Bo Zhao
To address this problem, we present a new image reconstruction method for MR Fingerprinting, integrating low-rank and subspace modeling with a deep generative prior.
no code implementations • 8 Oct 2021 • Malte Hoffmann, Esra Abaci Turk, Borjan Gagoski, Leah Morgan, Paul Wighton, M. Dylan Tisdall, Martin Reuter, Elfar Adalsteinsson, P. Ellen Grant, Lawrence L. Wald, André J. W. van der Kouwe
In fetal-brain MRI, head-pose changes between prescription and acquisition present a challenge to obtaining the standard sagittal, coronal and axial views essential to clinical assessment.
no code implementations • 8 Aug 2018 • Berkin Bilgic, Itthi Chatnuntawech, Mary Kate Manhard, Qiyuan Tian, Congyu Liao, Stephen F. Cauley, Susie Y. Huang, Jonathan R. Polimeni, Lawrence L. Wald, Kawin Setsompop
While msEPI can mitigate these artifacts, high-quality msEPI has been elusive because of phase mismatch arising from shot-to-shot variations which preclude the combination of the multiple-shot data into a single image.
no code implementations • 23 Oct 2017 • Bo Zhao, Justin P. Haldar, Congyu Liao, Dan Ma, Yun Jiang, Mark A. Griswold, Kawin Setsompop, Lawrence L. Wald
Magnetic resonance (MR) fingerprinting is a new quantitative imaging paradigm, which simultaneously acquires multiple MR tissue parameter maps in a single experiment.
Signal Processing