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Related papers: LARO: Learned Acquisition and Reconstruction Optim…

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Purpose: To develop a method for rapid sub-millimeter T1, T2, T2* and QSM mapping in a single scan using multi-contrast Learned Acquisition and Reconstruction Optimization (mcLARO). Methods: A pulse sequence was developed by interleaving…

Image and Video Processing · Electrical Eng. & Systems 2023-11-28 Jinwei Zhang , Thanh D. Nguyen , Eddy Solomon , Chao Li , Qihao Zhang , Jiahao Li , Hang Zhang , Pascal Spincemaille , Yi Wang

Quantitative imaging in MRI usually involves acquisition and reconstruction of a series of images at multi-echo time points, which possibly requires more scan time and specific reconstruction technique compared to conventional qualitative…

Signal Processing · Electrical Eng. & Systems 2021-03-11 Jinwei Zhang , Hang Zhang , Chao Li , Pascal Spincemaille , Mert Sabuncu , Thanh D. Nguyen , Yi Wang

Accelerated MRI involves collecting partial $k$-space measurements to reduce acquisition time, patient discomfort, and motion artifacts, and typically uses regular undersampling patterns or human-designed schemes. Recent works have studied…

Image and Video Processing · Electrical Eng. & Systems 2026-05-20 Siddhant Gautam , Angqi Li , Nicole Seiberlich , Jeffrey A. Fessler , Saiprasad Ravishankar

Quantitative susceptibility mapping (QSM) is an MRI phase-based post-processing method that quantifies tissue magnetic susceptibility distributions. However, QSM acquisitions are relatively slow, even with parallel imaging. Incoherent…

Image and Video Processing · Electrical Eng. & Systems 2021-07-20 Yang Gao , Martijn Cloos , Feng Liu , Stuart Crozier , G. Bruce Pike , Hongfu Sun

Acquisition of Magnetic Resonance Imaging (MRI) scans can be accelerated by under-sampling in k-space (i.e., the Fourier domain). In this paper, we consider the problem of optimizing the sub-sampling pattern in a data-driven fashion. Since…

Image and Video Processing · Electrical Eng. & Systems 2019-05-02 Cagla Deniz Bahadir , Adrian V. Dalca , Mert R. Sabuncu

The inherent slow imaging speed of Magnetic Resonance Image (MRI) has spurred the development of various acceleration methods, typically through heuristically undersampling the MRI measurement domain known as k-space. Recently, deep neural…

Image and Video Processing · Electrical Eng. & Systems 2022-04-13 Wei Peng , Li Feng , Guoying Zhao , Fang Liu

Multi-echo magnetic resonance (MR) images are acquired by changing the echo times (for T2 weighted) or relaxation times (for T1 weighted) of scans. The resulting (multi-echo) images are usually used for quantitative MR imaging. Acquiring MR…

Machine Learning · Computer Science 2019-12-11 Vanika Singhal , Angshul Majumdar

Despite its exceptional soft tissue contrast, Magnetic Resonance Imaging (MRI) faces the challenge of long scanning times compared to other modalities like X-ray radiography. Shortening scanning times is crucial in clinical settings, as it…

Machine Learning · Computer Science 2023-12-08 Thomas Sanchez

Magnetic Resonance Imaging (MRI) is considered today the golden-standard modality for soft tissues. The long acquisition times, however, make it more prone to motion artifacts as well as contribute to the relatively high costs of this…

Image and Video Processing · Electrical Eng. & Systems 2020-04-07 Tomer Weiss , Sanketh Vedula , Ortal Senouf , Oleg Michailovich , Michael Zibulevsky , Alex Bronstein

Magnetic Resonance Imaging (MRI) acquisitions require extensive scan times, limiting patient throughput and increasing susceptibility to motion artifacts. Accelerated parallel MRI techniques reduce acquisition time by undersampling k-space…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Mingi Kang

Sample efficiency remains a key challenge in multi-agent reinforcement learning (MARL). A promising approach is to learn a meaningful latent representation space through auxiliary learning objectives alongside the MARL objective to aid in…

Multiagent Systems · Computer Science 2024-06-06 Dom Huh , Prasant Mohapatra

To develop a deep-learning method for achieving fast high-resolution MR elastography from highly undersampled data without the need of high-quality training dataset. We first framed the deep neural network representation as a nonlinear…

Signal Processing · Electrical Eng. & Systems 2026-01-21 Xi Peng

Cardiac MRI is limited by long acquisition times, which can lead to patient discomfort and motion artifacts. We aim to accelerate Cartesian dynamic cardiac MRI by learning efficient, scan-adaptive undersampling patterns that preserve…

Image and Video Processing · Electrical Eng. & Systems 2026-02-24 Siddhant Gautam , Angqi Li , Prachi P. Agarwal , Anil K. Attili , Jeffrey A. Fessler , Nicole Seiberlich , Saiprasad Ravishankar

Quantitative T1rho mapping has shown promise in clinical and research studies. However, it suffers from long scan times. Deep learning-based techniques have been successfully applied in accelerated quantitative MR parameter mapping.…

Image and Video Processing · Electrical Eng. & Systems 2024-07-25 Yuanyuan Liu , Jinwen Xie , Zhuo-Xu Cui , Qingyong Zhu , Jing Cheng , Dong Liang , Yanjie Zhu

Accelerated Magnetic Resonance Imaging (MRI) requires careful optimization of k-space sampling patterns to balance acquisition speed and image quality. While recent advances in deep learning have shown promise in optimizing Cartesian…

Tissues and Organs · Quantitative Biology 2025-08-15 Ruru Xu , Ilkay Oksuz

22. Shortening acquisition time and reducing the motion-artifact are two of the most critical issues in MRI. As a promising solution, high-quality MRI image restoration provides a new approach to achieve higher resolution without costing…

Image and Video Processing · Electrical Eng. & Systems 2021-02-02 Hao Li , Jianan Liu

Recent medical image reconstruction techniques focus on generating high-quality medical images suitable for clinical use at the lowest possible cost and with the fewest possible adverse effects on patients. Recent works have shown…

Image and Video Processing · Electrical Eng. & Systems 2025-01-07 Shijun Liang , Anish Lahiri , Saiprasad Ravishankar

Accelerated magnetic resonance imaging resorts to either Fourier-domain subsampling or better reconstruction algorithms to deal with fewer measurements while still generating medical images of high quality. Determining the optimal sampling…

Machine Learning · Computer Science 2023-08-30 Zhishen Huang

Magnetic Resonance Imaging (MRI) has long been considered to be among "the gold standards" of diagnostic medical imaging. The long acquisition times, however, render MRI prone to motion artifacts, let alone their adverse contribution to the…

Image and Video Processing · Electrical Eng. & Systems 2021-04-14 Tomer Weiss , Ortal Senouf , Sanketh Vedula , Oleg Michailovich , Michael Zibulevsky , Alex Bronstein

Multiple-input multiple-output (MIMO) radar is one of the leading depth sensing modalities. However, the usage of multiple receive channels lead to relative high costs and prevent the penetration of MIMOs in many areas such as the…

Signal Processing · Electrical Eng. & Systems 2021-10-08 Tomer Weiss , Nissim Peretz , Sanketh Vedula , Arie Feuer , Alex Bronstein
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