Xi Peng

Assistant Professor

Iowa State University

United States

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About

Dr. Xi Peng is an Assistant Professor at the University of Iowa, specializing in advancements in magnetic resonance imaging and image reconstruction techniques. His research interests include high-dimensional MR reconstruction, machine learning applications in imaging, and efficient algorithms for MRI. Recent publications highlight his contributions to integrating physics-based modeling with data-driven approaches and improving regularization methods in image reconstruction.

Articles (12)

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2024

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2024

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2024

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2023

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2023

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2023

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2023

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2022

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2022

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2021

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2021

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2020

Collaborators (4)

Bradley Sutton

University of Illinois at Urbana-Champaign

UNITED STATES

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Hengfa Lu

University of Texas at Austin

UNITED STATES

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Leslie Ying

State University of New York at Buffalo

UNITED STATES

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Bo Zhao

Assistant Professor

University of Texas at Austin

UNITED STATES

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Xi Peng

Research Interests

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About

Articles (12)

High-Dimensional MR Reconstruction Integrating Subspace and Adaptive Generative Models

Learning-Assisted Fast Determination of Regularization Parameter in Constrained Image Reconstruction

Simultaneous brain and neck time-of-flight MRA using spiral multiband with localized quadratic encoding

Corrigendum to “Incorporating reference guided priors into calibrationless parallel imaging reconstruction” [Magn. Reson. Imaging, 57, April 2019, 347–358] (Magnetic Resonance Imaging (2019) 57 (347–358), (S0730725X18301152), (10.1016/j.mri.2018.12.006))

Evaluating efficient SENSE algorithms to deblur spiral MRI with fat/water separation

High-Dimensional MR Spatiospectral Imaging by Integrating Physics-Based Modeling and Data-Driven Machine Learning: Current progress and future directions

JSENSE-Pro: Joint sensitivity estimation and image reconstruction in parallel imaging using pre-learned subspaces of coil sensitivity functions

DeepSENSE: Learning coil sensitivity functions for SENSE reconstruction using deep learning

Accelerated MRI Reconstruction With Separable and Enhanced Low-Rank Hankel Regularization

A 4-minute solution for submillimeter whole-brain T<inf>1ρ</inf> quantification

Fast 3D MR elastography of the whole brain using spiral staircase: Data acquisition, image reconstruction, and joint deblurring

Constrained Magnetic Resonance Spectroscopic Imaging by Learning Nonlinear Low-Dimensional Models

Collaborators (4)

Bradley Sutton

Hengfa Lu

Leslie Ying

Bo Zhao

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