ESPRESO: An algorithm to estimate the slice profile of a single magnetic resonance image

Shuo Han, Samuel W. Remedios, Michael Schär, Aaron Carass, Jerry L. Prince

Research output: Contribution to journalArticlepeer-review


To reduce scan time, magnetic resonance (MR) images are often acquired using 2D multi-slice protocols with thick slices that may also have gaps between them. The resulting image volumes have lower resolution in the through-plane direction than in the in-plane direction, and the through-plane resolution is in part characterized by the protocol's slice profile which acts as a through-plane point spread function (PSF). Although super-resolution (SR) has been shown to improve the visualization and down-stream processing of 2D multi-slice MR acquisitions, previous algorithms are usually unaware of the true slice profile, which may lead to sub-optimal SR performance. In this work, we present an algorithm to estimate the slice profile of a 2D multi-slice acquisition given only its own image volume without any external training data. We assume that an anatomical image is isotropic in the sense that, after accounting for a correctly estimated slice profile, the image patches along different orientations have the same probability distribution. Our proposed algorithm uses a modified generative adversarial network (GAN) where the generator network estimates the slice profile to reduce the resolution of the in-plane direction, and the discriminator network determines whether a direction is generated or real low resolution. The proposed algorithm, ESPRESO, which stands for “estimating the slice profile for resolution enhancement of a single image only”, was tested with a state-of-the-art internally supervised SR algorithm. Specifically, ESPRESO is used to create training data for this SR algorithm, and results show improvements when ESPRESO is used over commonly-used PSFs.

Original languageEnglish (US)
Pages (from-to)155-163
Number of pages9
JournalMagnetic Resonance Imaging
StatePublished - May 2023


  • GAN
  • MRI
  • Slice profile
  • Super-resolution

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging
  • Biomedical Engineering


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