Spatio-temporal TGV denoising for ASL perfusion imaging

Neuroimage. 2017 Aug 15;157:81-96. doi: 10.1016/j.neuroimage.2017.05.054. Epub 2017 May 27.

Abstract

In arterial spin labeling (ASL) a perfusion weighted image is achieved by subtracting a label image from a control image. This perfusion weighted image has an intrinsically low signal to noise ratio and numerous measurements are required to achieve reliable image quality, especially at higher spatial resolutions. To overcome this limitation various denoising approaches have been published using the perfusion weighted image as input for denoising. In this study we propose a new spatio-temporal filtering approach based on total generalized variation (TGV) regularization which exploits the inherent information of control and label pairs simultaneously. In this way, the temporal and spatial similarities of all images are used to jointly denoise the control and label images. To assess the effect of denoising, virtual ground truth data were produced at different SNR levels. Furthermore, high-resolution in-vivo pulsed ASL data sets were acquired and processed. The results show improved image quality, quantitative accuracy and robustness against outliers compared to seven state of the art denoising approaches.

Keywords: ASL; Arterial spin labeling; CBF; Cerebral blood flow; Denoising; MRI.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Brain / diagnostic imaging*
  • Cerebrovascular Circulation / physiology*
  • Female
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Magnetic Resonance Imaging / methods*
  • Male
  • Perfusion Imaging / methods*
  • Spin Labels
  • Young Adult

Substances

  • Spin Labels