@inproceedings{4abd5917d3784bae86ada2f78d63db1f,
title = "MR Slice Profile Estimation by Learning to Match Internal Patch Distributions",
abstract = "To super-resolve the through-plane direction of a multi-slice 2D magnetic resonance (MR) image, its slice selection profile can be used as the degeneration model from high resolution (HR) to low resolution (LR) to create paired data when training a supervised algorithm. Existing super-resolution algorithms make assumptions about the slice selection profile since it is not readily known for a given image. In this work, we estimate a slice selection profile given a specific image by learning to match its internal patch distributions. Specifically, we assume that after applying the correct slice selection profile, the image patch distribution along HR in-plane directions should match the distribution along the LR through-plane direction. Therefore, we incorporate the estimation of a slice selection profile as part of learning a generator in a generative adversarial network (GAN). In this way, the slice selection profile can be learned without any external data. Our algorithm was tested using simulations from isotropic MR images, incorporated in a through-plane super-resolution algorithm to demonstrate its benefits, and also used as a tool to measure image resolution. Our code is at https://github.com/shuohan/espreso2.",
keywords = "GAN, MRI, Slice profile, Super resolution",
author = "Shuo Han and Samuel Remedios and Aaron Carass and Michael Sch{\"a}r and Prince, {Jerry L.}",
note = "Funding Information: Acknowledgments. This work was supported by a 2019 Johns Hopkins Discovery Award and NMSS Grant RG-1907-34570. Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 27th International Conference on Information Processing in Medical Imaging, IPMI 2021 ; Conference date: 28-06-2021 Through 30-06-2021",
year = "2021",
doi = "10.1007/978-3-030-78191-0_9",
language = "English (US)",
isbn = "9783030781903",
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 = "108--119",
editor = "Aasa Feragen and Stefan Sommer and Julia Schnabel and Mads Nielsen",
booktitle = "Information Processing in Medical Imaging - 27th International Conference, IPMI 2021, Proceedings",
address = "Germany",
}