@inproceedings{69f04a93fee347eab3d7a951db7efa08,
title = "T1/T2 Relaxation Temporal Modelling from Accelerated Acquisitions Using a Latent Transformer",
abstract = "Quantitative cardiac magnetic resonance T1 and T2 mapping enable myocardial tissue characterisation but the lengthy scan times restrict their widespread clinical application. We propose a deep learning method that incorporates a time dependency Latent Transformer module to model relationships between parameterised time frames for improved reconstruction from undersampled data. The module, implemented as a multi-resolution sequence-to-sequence transformer, is integrated into an encoder-decoder architecture to leverage the inherent temporal correlations in relaxation processes. The presented results for accelerated T1 and T2 mapping show the model recovers maps with higher fidelity by explicit incorporation of time dynamics. This work demonstrates the importance of temporal modelling for artifact-free reconstruction in quantitative MRI.",
keywords = "Deep learning, MRI reconstruction, Quantitative MRI",
author = "Michael T{\"a}nzer and Fanwen Wang and Mengyun Qiao and Wenjia Bai and Daniel Rueckert and Guang Yang and Sonia Nielles-Vallespin",
note = "Publisher Copyright: {\textcopyright} 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 14th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2023 held in Conjunction with MICCAI 2023 ; Conference date: 12-10-2023 Through 12-10-2023",
year = "2024",
doi = "10.1007/978-3-031-52448-6_28",
language = "English",
isbn = "9783031524479",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "293--302",
editor = "Oscar Camara and Esther Puyol-Ant{\'o}n and Avan Suinesiaputra and Alistair Young and Maxime Sermesant and Qian Tao and Chengyan Wang",
booktitle = "Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers - 14th International Workshop, STACOM 2023, Held in Conjunction with MICCAI 2023, Revised Selected Papers",
}