Automatic intervertebral disc localization and segmentation in 3D MR images based on regression forests and active contours

Martin Urschler, Kerstin Hammernik, Thomas Ebner, Darko Stern

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

Abstract

We introduce a fully automatic localization and segmentation pipeline for three-dimensional (3D) intervertebral discs (IVDs), consisting of a regression-based prediction of vertebral bodies and IVD positions as well as a 3D geodesic active contour segmentation delineating the IVDs. The approach was evaluated on the data set of the challenge in conjunction with the 3rd MICCAI Workshop & Challenge on Computational Methods and Clinical Applications for Spine Imaging -MICCAI– CSI2015, that consists of 15 magnetic resonance images of the lumbar spine with given ground truth segmentations. Based on a localization accuracy of 3.9±1.6 mm, we achieve segmentation results in terms of the Dice similarity coefficient of 89.1 ±2.9% averaged over the whole data set.

LanguageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag Heidelberg
Pages130-140
Number of pages11
Volume9402
ISBN (Print)9783319418261
DOIs
StatusPublished - 2016
EventInternational Conference on Medical Image Computing and Computer Assisted Intervention - Munich, Germany
Duration: 5 Oct 20159 Oct 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9402
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

ConferenceInternational Conference on Medical Image Computing and Computer Assisted Intervention
CountryGermany
CityMunich
Period5/10/159/10/15

Fingerprint

Active Contours
Magnetic resonance
Computational methods
Segmentation
Pipelines
Regression
Imaging techniques
Spine
Similarity Coefficient
Dice
Magnetic Resonance Image
Computational Methods
Geodesic
Imaging
Three-dimensional
Prediction

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Fields of Expertise

  • Information, Communication & Computing

Cooperations

  • BioTechMed-Graz

Cite this

Urschler, M., Hammernik, K., Ebner, T., & Stern, D. (2016). Automatic intervertebral disc localization and segmentation in 3D MR images based on regression forests and active contours. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9402, pp. 130-140). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9402). Springer Verlag Heidelberg. https://doi.org/10.1007/978-3-319-41827-8_13

Automatic intervertebral disc localization and segmentation in 3D MR images based on regression forests and active contours. / Urschler, Martin; Hammernik, Kerstin; Ebner, Thomas; Stern, Darko.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9402 Springer Verlag Heidelberg, 2016. p. 130-140 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9402).

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

Urschler, M, Hammernik, K, Ebner, T & Stern, D 2016, Automatic intervertebral disc localization and segmentation in 3D MR images based on regression forests and active contours. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 9402, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9402, Springer Verlag Heidelberg, pp. 130-140, International Conference on Medical Image Computing and Computer Assisted Intervention, Munich, Germany, 5/10/15. https://doi.org/10.1007/978-3-319-41827-8_13
Urschler M, Hammernik K, Ebner T, Stern D. Automatic intervertebral disc localization and segmentation in 3D MR images based on regression forests and active contours. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9402. Springer Verlag Heidelberg. 2016. p. 130-140. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-41827-8_13
Urschler, Martin ; Hammernik, Kerstin ; Ebner, Thomas ; Stern, Darko. / Automatic intervertebral disc localization and segmentation in 3D MR images based on regression forests and active contours. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9402 Springer Verlag Heidelberg, 2016. pp. 130-140 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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