Skip to main content

Assessing Out-of-the-box Software for Automated Hippocampus Segmentation

  • Conference paper
Book cover Bildverarbeitung für die Medizin 2016

Part of the book series: Informatik aktuell ((INFORMAT))

Abstract

A comparison of four out-of-the-box software packages for automated hippocampus segmentation reveals that AHEAD and Freesurfer deliver the most satisfying results in terms of software usability and segmentation reliability and are thus recommended to be used in a fused manner.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Fotuhi M, Do D, Jack C. Modifiable factors that alter the size of the hippocampus with ageing. Nat Rev Neurol. 2012;8:189–202.

    Google Scholar 

  2. Malmgren K, Thom M. Hippocampal sclerosis: origins and imaging. Epilepsia. 2012;53:19–33.

    Article  Google Scholar 

  3. Teipel S, Grothe M, Lista S, et al. Relevance of magnetic resonance imaging for early detection and diagnosis of alzheimer disease. Med Clin North Am. 2013;97:399–424.

    Article  Google Scholar 

  4. Fischl B, van der Kouwe A, Destrieux C, et al. Automatically parcellating the human cerebral cortex. Cereb Cortex. 2004;14(1):11–22.

    Article  Google Scholar 

  5. Suh JW, Wang H, Das S, et al. Automatic segmentation of the hippocampus in T1- Weighted MRI with multi-atlas label fusion using open source software: evaluation in 1.5 and 3.0 T ADNI MRI. Proc Int Soc Magn Reson Med Con (ISMRM). 2011.

    Google Scholar 

  6. Zarpalas D, Gkontra P, Daras P, et al. Accurate and fully automatic hippocampus segmentation using subject-specific 3D optimal local maps into a hybrid active contour model. IEEE J Trans Eng Health Med. 2014;2:1–16.

    Article  Google Scholar 

  7. Jafari-Khouzani K, Elisevich K, Patel S, et al. Database of magnetic resonance images of nonepileptic subjects and temporal lobe epilepsy patients for validation of hippocampal segmentation techniques. Neuroinformatics. 2011;9(4):335–46.

    Article  Google Scholar 

  8. Cherbuin N, Anstey1 KJ, Réglade-Meslin C, et al. In vivo hippocampal measurement and memory: a comparison of manual tracing and automated segmentation in a large community-based sample. PLoS ONE. 2009;4:1–10.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Gschwandtner, M., Höller, Y., Liedlgruber, M., Trinka, E., Uhl, A. (2016). Assessing Out-of-the-box Software for Automated Hippocampus Segmentation. In: Tolxdorff, T., Deserno, T., Handels, H., Meinzer, HP. (eds) Bildverarbeitung für die Medizin 2016. Informatik aktuell. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49465-3_38

Download citation

Publish with us

Policies and ethics