Dynamic volume reconstruction from multi-slice abdominal MRI using manifold alignment

Xin Chen*, Muhammad Usman, Daniel R. Balfour, Paul K. Marsden, Andrew J. Reader, Claudia Prieto , Andrew P. King

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

2 Citations (Scopus)

Abstract

We present a novel framework for retrospective dynamic 3D volume reconstruction from a multi-slice MRI acquisition using manifold alignment. K-space data are continuously acquired under free breathing using a radial golden-angle trajectory in a slice-by-slice manner. Non-overlapping consecutive profiles that were acquired within a short time window are grouped together. All grouped profiles from all slices are then simultaneously embedded using manifold alignment into a common manifold space (MS),in which profiles that were acquired at similar respiratory states are close together. Subsequently,a 3D volume can be reconstructed at each of the grouped profile MS positions by combining profiles that are close in the MS. This enables the original multi-slice dataset to be used to reconstruct a dynamic 3D sequence based on the respiratory state correspondences established in the MS. Our method was evaluated on both synthetic and in vivo datasets. For the synthetic datasets,the reconstructed dynamic sequence achieved a normalised cross correlation of 0.98 and peak signal to noise ratio of 26.64 dB compared with the ground truth. For the in vivo datasets,based on sharpness measurements and visual comparison,our method performed better than reconstruction using an adapted central k-space gating method.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer‐Verlag Berlin Heidelberg
Pages493-501
Number of pages9
Volume9902 LNCS
ISBN (Print)9783319467252
DOIs
Publication statusE-pub ahead of print - 2 Oct 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9902 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Keywords

  • Dynamic 3D volume reconstruction
  • Manifold alignment
  • MRI
  • Respiratory motion estimation

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