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Title:

Data augmentation for deep learning based accelerated MRI reconstruction with limited data

Document type:
Konferenzbeitrag
Author(s):
Fabian, Zalan; Heckel, Reinhard; Soltanolkotabi, Mahdi
Abstract:
Deep neural networks have emerged as very successful tools for image restoration and reconstruction tasks. These networks are often trained end-to-end to directly reconstruct an image from a noisy or corrupted measurement of that image. To achieve state-of-the-art performance, training on large and diverse sets of images is considered critical. However, it is often difficult and/or expensive to collect large amounts of training images. Inspired by the success of Data Augmentation (DA) for classi...     »
Editor:
Meila, Marina; Zhang, Tong
Book / Congress title:
Proceedings of the 38th International Conference on Machine Learning
Volume:
139
Publisher:
PMLR
Year:
2021
Pages:
3057--3067
Bookseries title:
Proceedings of Machine Learning Research
WWW:
https://proceedings.mlr.press/v139/fabian21a.html
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