Non-linear realignment improves hippocampus subfield segmentation reliability

Neuroimage. 2019 Dec:203:116206. doi: 10.1016/j.neuroimage.2019.116206. Epub 2019 Sep 17.

Abstract

Participant movement can deleteriously affect MR image quality. Further, for the visualization and segmentation of small anatomical structures, there is a need to improve image quality, specifically signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), by acquiring multiple anatomical scans consecutively. We aimed to ameliorate movement artefacts and increase SNR in a high-resolution turbo spin-echo (TSE) sequence acquired thrice using non-linear realignment in order to improve segmentation consistency of the hippocampus subfields. We assessed the method in 29 young healthy participants, 11 Motor Neuron Disease patients, and 11 age matched controls at 7T, and 24 healthy adolescents at 3T. Results show improved image segmentation of the hippocampus subfields when comparing template-based segmentations with individual segmentations with Dice overlaps N = 75; ps < 0.001 (Friedman's test) and higher sharpness ps < 0.001 in non-linearly realigned scans as compared to linearly, and arithmetically averaged scans.

Keywords: Cornu ammonis; Hippocampus subfields; Magnetic resonance imaging; Motion correction; Realignment; Segmentation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Artifacts
  • Hippocampus / anatomy & histology
  • Hippocampus / diagnostic imaging*
  • Hippocampus / pathology
  • Humans
  • Image Enhancement / methods*
  • Image Processing, Computer-Assisted / methods*
  • Magnetic Resonance Imaging*
  • Middle Aged
  • Motor Neuron Disease / diagnostic imaging
  • Motor Neuron Disease / pathology
  • Reproducibility of Results
  • Signal-To-Noise Ratio