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Segmentation of Intervertebral Discs in 3D MRI Data Using Multi-atlas Based Registration
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Sectra, Linkoping, Sweden.ORCID iD: 0000-0002-0442-3524
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV). Sectra, Linkoping, Sweden.ORCID iD: 0000-0003-0908-9470
2016 (English)In: Computational Methods and Clinical Applications for Spine Imaging, CSI 2015, SPRINGER INT PUBLISHING AG , 2016, Vol. 9402, 107-116 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents one of the participating methods to the intervertebral disc segmentation challenge organized in conjunction with the 3rd MICCAI Workshop amp; Challenge on Computational Methods and Clinical Applications for Spine Imaging - MICCAI-CSI2015. The presented method consist of three steps. In the first step, vertebral bodies are detected and labeled using integral channel features and a graphical parts model. The second step consists of image registration, where a set of image volumes with corresponding intervertebral disc atlases are registered to the target volume using the output from the first step as initialization. In the final step, the registered atlases are combined using label fusion to derive the final segmentation. The pipeline was evaluated using a set of 15 + 10 T2-weighted image volumes provided as training and test data respectively for the segmentation challenge. For the training data, a mean disc centroid distance of 0.86 mm and an average DICE score of 91% was achieved, and for the test data the corresponding results were 0.90 mm and 90%.

Place, publisher, year, edition, pages
SPRINGER INT PUBLISHING AG , 2016. Vol. 9402, 107-116 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-133548DOI: 10.1007/978-3-319-41827-8_10ISI: 000389504400010ISBN: 978-3-319-41827-8; 978-3-319-41826-1 (print)OAI: oai:DiVA.org:liu-133548DiVA: diva2:1060852
Conference
3rd International Workshop and Challenge on Computational Methods and Clinical Applications for Spine Imaging (CSI)
Available from: 2016-12-30 Created: 2016-12-29 Last updated: 2016-12-30

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Wang, ChunliangForsberg, Daniel
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Division of Radiological SciencesFaculty of Medicine and Health SciencesCenter for Medical Image Science and Visualization (CMIV)Media and Information TechnologyThe Institute of Technology
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