A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction

Schlemper J, Caballero J, Hajnal JV, Price AN, Rueckert D (2018)

Publication Type: Journal article

Publication year: 2018

Journal

IEEE Transactions on Medical Imaging Institute of Electrical and Electronics Engineers (IEEE)

Book Volume: 37

Pages Range: 491-503

Article Number: 8067520

Journal Issue: 2

DOI: 10.1109/TMI.2017.2760978

Abstract

Inspired by recent advances in deep learning, we propose a framework for reconstructing dynamic sequences of 2-D cardiac magnetic resonance (MR) images from undersampled data using a deep cascade of convolutional neural networks (CNNs) to accelerate the data acquisition process. In particular, we address the case where data are acquired using aggressive Cartesian undersampling. First, we show that when each 2-D image frame is reconstructed independently, the proposed method outperforms state-of-the-art 2-D compressed sensing approaches, such as dictionary learning-based MR image reconstruction, in terms of reconstruction error and reconstruction speed. Second, when reconstructing the frames of the sequences jointly, we demonstrate that CNNs can learn spatio-temporal correlations efficiently by combining convolution and data sharing approaches. We show that the proposed method consistently outperforms state-of-the-art methods and is capable of preserving anatomical structure more faithfully up to 11-fold undersampling. Moreover, reconstruction is very fast: each complete dynamic sequence can be reconstructed in less than 10 s and, for the 2-D case, each image frame can be reconstructed in 23 ms, enabling real-time applications.

Involved external institutions

Imperial College London / The Imperial College of Science, Technology and Medicine GB United Kingdom (GB) King’s College London GB United Kingdom (GB)

How to cite

APA:

Schlemper, J., Caballero, J., Hajnal, J.V., Price, A.N., & Rueckert, D. (2018). A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction. IEEE Transactions on Medical Imaging, 37(2), 491-503. https://doi.org/10.1109/TMI.2017.2760978

MLA:

Schlemper, Jo, et al. "A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction." IEEE Transactions on Medical Imaging 37.2 (2018): 491-503.

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