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Brain Imaging and Behavior

, Volume 12, Issue 6, pp 1678–1695 | Cite as

A comparative study of segmentation techniques for the quantification of brain subcortical volume

  • Theophilus N. AkudjeduEmail author
  • Leila Nabulsi
  • Migle Makelyte
  • Cathy Scanlon
  • Sarah Hehir
  • Helen Casey
  • Srinath Ambati
  • Joanne Kenney
  • Stefani O’Donoghue
  • Emma McDermott
  • Liam Kilmartin
  • Peter Dockery
  • Colm McDonald
  • Brian Hallahan
  • Dara M. Cannon
ORIGINAL RESEARCH

Abstract

Manual tracing of magnetic resonance imaging (MRI) represents the gold standard for segmentation in clinical neuropsychiatric research studies, however automated approaches are increasingly used due to its time limitations. The accuracy of segmentation techniques for subcortical structures has not been systematically investigated in large samples. We compared the accuracy of fully automated [(i) model-based: FSL-FIRST; (ii) patch-based: volBrain], semi–automated (FreeSurfer) and stereological (Measure®) segmentation techniques with manual tracing (ITK-SNAP) for delineating volumes of the caudate (easy-to-segment) and the hippocampus (difficult-to-segment). High resolution 1.5 T T1-weighted MR images were obtained from 177 patients with major psychiatric disorders and 104 healthy participants. The relative consistency (partial correlation), absolute agreement (intraclass correlation coefficient, ICC) and potential technique bias (Bland–Altman plots) of each technique was compared with manual segmentation. Each technique yielded high correlations (0.77–0.87, p < 0.0001) and moderate ICC’s (0.28–0.49) relative to manual segmentation for the caudate. For the hippocampus, stereology yielded good consistency (0.52–0.55, p < 0.0001) and ICC (0.47–0.49), whereas automated and semi-automated techniques yielded poor ICC (0.07–0.10) and moderate consistency (0.35–0.62, p < 0.0001). Bias was least using stereology for segmentation of the hippocampus and using FreeSurfer for segmentation of the caudate. In a typical neuropsychiatric MRI dataset, automated segmentation techniques provide good accuracy for an easy-to-segment structure such as the caudate, whereas for the hippocampus, a reasonable correlation with volume but poor absolute agreement was demonstrated. This indicates manual or stereological volume estimation should be considered for studies that require high levels of precision such as those with small sample size.

Keywords

Segmentation techniques Stereology Subcortical structures FreeSurfer FSL-FIRST VolBrain 

Notes

Acknowledgements

TNA’s doctoral training is funded by the College of Medicine, Nursing and Health Sciences Postgraduate Scholarship Scheme, NUI Galway (2016–2020). We would also like to thank all of the participants and their families for their involvement in the Research Programme of the Clinical Neuroimaging laboratory, NUI Galway.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

All participants provided written informed consent for the relevant studies.

Supplementary material

11682_2018_9835_MOESM1_ESM.doc (8.8 mb)
Supplementary material 1 (DOC 9035 KB)

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Authors and Affiliations

  • Theophilus N. Akudjedu
    • 1
    Email author return OK on get
  • Leila Nabulsi
    • 1
  • Migle Makelyte
    • 1
    • 2
  • Cathy Scanlon
    • 1
  • Sarah Hehir
    • 1
  • Helen Casey
    • 1
  • Srinath Ambati
    • 1
  • Joanne Kenney
    • 1
  • Stefani O’Donoghue
    • 1
  • Emma McDermott
    • 1
  • Liam Kilmartin
    • 2
  • Peter Dockery
    • 1
  • Colm McDonald
    • 1
  • Brian Hallahan
    • 1
  • Dara M. Cannon
    • 1
  1. 1.Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, Psychiatry & Anatomy, School of Medicine,College of Medicine Nursing and Health SciencesNational University of Ireland GalwayGalwayIreland
  2. 2.College of Engineering and InformaticsNational University of Ireland GalwayGalwayIreland

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