CMRxRecon2024: A Multi-Modality, Multi-View K-Space Dataset Boosting Universal Machine Learning for Accelerated Cardiac MRI

1 code implementation • 27 Jun 2024 • Zi Wang, Fanwen Wang, Chen Qin, Jun Lyu, Ouyang Cheng, Shuo Wang, Yan Li, Mengyao Yu, Haoyu Zhang, Kunyuan Guo, Zhang Shi, Qirong Li, Ziqiang Xu, Yajing Zhang, Hao Li, Sha Hua, Binghua Chen, Longyu Sun, Mengting Sun, Qin Li, Ying-Hua Chu, Wenjia Bai, Jing Qin, Xiahai Zhuang, Claudia Prieto, Alistair Young, Michael Markl, He Wang, Lianming Wu, Guang Yang, Xiaobo Qu, Chengyan Wang

To the best of our knowledge, the CMRxRecon2024 dataset is the largest and most diverse publicly available cardiac k-space dataset.

MRI Reconstruction

A deep learning approach to using wearable seismocardiography (SCG) for diagnosing aortic valve stenosis and predicting aortic hemodynamics obtained by 4D flow MRI

no code implementations • 5 Jan 2023 • Mahmoud E. Khani, Ethan M. I. Johnson, Aparna Sodhi, Joshua Robinson, Cynthia K. Rigsby, Bradly D. Allen, Michael Markl

We also investigated the ability of this deep learning technique to differentiate between patients diagnosed with aortic valve stenosis (AS), non-AS patients with a bicuspid aortic valve (BAV), non-AS patients with a mechanical aortic valve (MAV), and healthy subjects with a normal tricuspid aortic valve (TAV).

Deep Learning

MRI-MECH: Mechanics-informed MRI to estimate esophageal health

no code implementations • 15 Sep 2022 • Sourav Halder, Ethan M. Johnson, Jun Yamasaki, Peter J. Kahrilas, Michael Markl, John E. Pandolfino, Neelesh A. Patankar

Dynamic magnetic resonance imaging (MRI) is a popular medical imaging technique to generate image sequences of the flow of a contrast material inside tissues and organs.

Machine-Learned Prediction Equilibrium for Dynamic Traffic Assignment

1 code implementation • 14 Sep 2021 • Lukas Graf, Tobias Harks, Kostas Kollias, Michael Markl

We study a dynamic traffic assignment model, where agents base their instantaneous routing decisions on real-time delay predictions.