Search Results for author: Dmitriy A. Yablonskiy

Found 3 papers, 1 papers with code

DiffGEPCI: 3D MRI Synthesis from mGRE Signals using 2.5D Diffusion Model

no code implementations29 Nov 2023 Yuyang Hu, Satya V. V. N. Kothapalli, Weijie Gan, Alexander L. Sukstanskii, Gregory F. Wu, Manu Goyal, Dmitriy A. Yablonskiy, Ulugbek S. Kamilov

We introduce a new framework called DiffGEPCI for cross-modality generation in magnetic resonance imaging (MRI) using a 2. 5D conditional diffusion model.

CoRRECT: A Deep Unfolding Framework for Motion-Corrected Quantitative R2* Mapping

no code implementations12 Oct 2022 Xiaojian Xu, Weijie Gan, Satya V. V. N. Kothapalli, Dmitriy A. Yablonskiy, Ulugbek S. Kamilov

Quantitative MRI (qMRI) refers to a class of MRI methods for quantifying the spatial distribution of biological tissue parameters.

Self-Supervised Learning

Learning-based Motion Artifact Removal Networks (LEARN) for Quantitative $R_2^\ast$ Mapping

1 code implementation3 Sep 2021 Xiaojian Xu, Satya V. V. N. Kothapalli, Jiaming Liu, Sayan Kahali, Weijie Gan, Dmitriy A. Yablonskiy, Ulugbek S. Kamilov

LEARN-IMG performs motion correction on mGRE images and relies on the subsequent analysis for the estimation of $R_2^\ast$ maps, while LEARN-BIO directly performs motion- and $B0$-inhomogeneity-corrected $R_2^\ast$ estimation.

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