Search Results for author: Congyu Liao

Found 11 papers, 3 papers with code

Artificial Intelligence for Neuro MRI Acquisition: A Review

no code implementations10 Jun 2024 Hongjia Yang, Guanhua Wang, Ziyu Li, Haoxiang Li, Jialan Zheng, Yuxin Hu, Xiaozhi Cao, Congyu Liao, Huihui Ye, Qiyuan Tian

Magnetic resonance imaging (MRI) has significantly benefited from the resurgence of artificial intelligence (AI).

Advancing low-field MRI with a universal denoising imaging transformer: Towards fast and high-quality imaging

1 code implementation30 Apr 2024 Zheren Zhu, Azaan Rehman, Xiaozhi Cao, Congyu Liao, Yoo Jin Lee, Michael Ohliger, Hui Xue, Yang Yang

Recent developments in low-field (LF) magnetic resonance imaging (MRI) systems present remarkable opportunities for affordable and widespread MRI access.

Denoising Diversity

3D-EPI Blip-Up/Down Acquisition (BUDA) with CAIPI and Joint Hankel Structured Low-Rank Reconstruction for Rapid Distortion-Free High-Resolution T2* Mapping

no code implementations1 Dec 2022 Zhifeng Chen, Congyu Liao, Xiaozhi Cao, Benedikt A. Poser, Zhongbiao Xu, Wei-Ching Lo, Manyi Wen, Jaejin Cho, Qiyuan Tian, Yaohui Wang, Yanqiu Feng, Ling Xia, Wufan Chen, Feng Liu, Berkin Bilgic

Purpose: This work aims to develop a novel distortion-free 3D-EPI acquisition and image reconstruction technique for fast and robust, high-resolution, whole-brain imaging as well as quantitative T2* mapping.

Image Reconstruction

Highly Accelerated EPI with Wave Encoding and Multi-shot Simultaneous Multi-Slice Imaging

1 code implementation3 Jun 2021 Jaejin Cho, Congyu Liao, Qiyuan Tian, Zijing Zhang, Jinmin Xu, Wei-Ching Lo, Benedikt A. Poser, V. Andrew Stenger, Jason Stockmann, Kawin Setsompop, Berkin Bilgic

We introduce wave encoded acquisition and reconstruction techniques for highly accelerated echo planar imaging (EPI) with reduced g-factor penalty and image artifacts.

SRDTI: Deep learning-based super-resolution for diffusion tensor MRI

1 code implementation17 Feb 2021 Qiyuan Tian, Ziyu Li, Qiuyun Fan, Chanon Ngamsombat, Yuxin Hu, Congyu Liao, Fuyixue Wang, Kawin Setsompop, Jonathan R. Polimeni, Berkin Bilgic, Susie Y. Huang

High-resolution diffusion tensor imaging (DTI) is beneficial for probing tissue microstructure in fine neuroanatomical structures, but long scan times and limited signal-to-noise ratio pose significant barriers to acquiring DTI at sub-millimeter resolution.


Robust Autocalibrated Structured Low-Rank EPI Ghost Correction

no code implementations30 Jul 2019 Rodrigo A. Lobos, W. Scott Hoge, Ahsan Javed, Congyu Liao, Kawin Setsompop, Krishna S. Nayak, Justin P. Haldar

First, it does not completely trust the information from autocalibration data, and instead considers the autocalibration and EPI data simultaneously when estimating low-rank matrix structure.

Highly Accelerated Multishot EPI through Synergistic Machine Learning and Joint Reconstruction

no code implementations8 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.

BIG-bench Machine Learning Image Reconstruction

Optimal Experiment Design for Magnetic Resonance Fingerprinting: Cramér-Rao Bound Meets Spin Dynamics

no code implementations23 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

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