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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.
Original language | English |
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Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Publisher | Springer Verlag Heidelberg |
Pages | 130-140 |
Number of pages | 11 |
Volume | 9402 |
ISBN (Print) | 9783319418261 |
DOIs | |
Publication status | Published - 2016 |
Event | International Conference on Medical Image Computing and Computer Assisted Intervention: MICCAI 2015 - Munich, Germany Duration: 5 Oct 2015 → 9 Oct 2015 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 9402 |
ISSN (Print) | 03029743 |
ISSN (Electronic) | 16113349 |
Conference
Conference | International Conference on Medical Image Computing and Computer Assisted Intervention |
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Country/Territory | Germany |
City | Munich |
Period | 5/10/15 → 9/10/15 |
ASJC Scopus subject areas
- General Computer Science
- Theoretical Computer Science
Fields of Expertise
- Information, Communication & Computing
Cooperations
- BioTechMed-Graz
Fingerprint
Dive into the research topics of 'Automatic intervertebral disc localization and segmentation in 3D MR images based on regression forests and active contours'. Together they form a unique fingerprint.Projects
- 1 Finished
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FWF - FAME - Fully Automatic MRI-based Age Estimation of Adolescents
Bischof, H. & Urschler, M.
1/07/15 → 31/12/18
Project: Research project