Evaluation and comparison of 3D intervertebral disc localization and segmentation methods for 3D T2 MR data: a grand challenge

Zheng, Guoyan, Chu, Chengwen, Belavy, Daniel L., Ibragimov, Bulat, Korez, Robert, Vrtovec, Tomaž, Hutt, Hugo, Everson, Richard, Meakin, Judith, Andrade, Isabel, Glocker, Ben, Chen, Hao, Dou, Qi, Heng, Pheng-Ann, Wang, Chunliang, Forsberg, Daniel, Neubert, Aleš, Fripp, Jurgen, Urschler, Martin, Stern, Darko, Wimmer, Maria, Novikov, Alexey A., Cheng, Hui, Armbrecht, Gabriele, Felsenberg, Dieter and Li, Shuo (2017) Evaluation and comparison of 3D intervertebral disc localization and segmentation methods for 3D T2 MR data: a grand challenge. Medical Image Analysis, 35 327-344. doi:10.1016/j.media.2016.08.005

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Author Zheng, Guoyan
Chu, Chengwen
Belavy, Daniel L.
Ibragimov, Bulat
Korez, Robert
Vrtovec, Tomaž
Hutt, Hugo
Everson, Richard
Meakin, Judith
Andrade, Isabel
Glocker, Ben
Chen, Hao
Dou, Qi
Heng, Pheng-Ann
Wang, Chunliang
Forsberg, Daniel
Neubert, Aleš
Fripp, Jurgen
Urschler, Martin
Stern, Darko
Wimmer, Maria
Novikov, Alexey A.
Cheng, Hui
Armbrecht, Gabriele
Felsenberg, Dieter
Li, Shuo
Title Evaluation and comparison of 3D intervertebral disc localization and segmentation methods for 3D T2 MR data: a grand challenge
Journal name Medical Image Analysis   Check publisher's open access policy
ISSN 1361-8423
Publication date 2017-01-01
Year available 2016
Sub-type Article (original research)
DOI 10.1016/j.media.2016.08.005
Open Access Status File (Author Post-print)
Volume 35
Start page 327
End page 344
Total pages 18
Place of publication Amsterdam, Netherlands
Publisher Elsevier BV
Language eng
Subject 3614 Radiological and Ultrasound Technology
2741 Radiology Nuclear Medicine and imaging
1707 Computer Vision and Pattern Recognition
2718 Health Informatics
1704 Computer Graphics and Computer-Aided Design
Abstract The evaluation of changes in Intervertebral Discs (IVDs) with 3D Magnetic Resonance (MR) Imaging (MRI) can be of interest for many clinical applications. This paper presents the evaluation of both IVD localization and IVD segmentation methods submitted to the Automatic 3D MRI IVD Localization and Segmentation challenge, held at the 2015 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2015) with an on-site competition. With the construction of a manually annotated reference data set composed of 25 3D T2-weighted MR images acquired from two different studies and the establishment of a standard validation framework, quantitative evaluation was performed to compare the results of methods submitted to the challenge. Experimental results show that overall the best localization method achieves a mean localization distance of 0.8 mm and the best segmentation method achieves a mean Dice of 91.8%, a mean average absolute distance of 1.1 mm and a mean Hausdorff distance of 4.3 mm, respectively. The strengths and drawbacks of each method are discussed, which provides insights into the performance of different IVD localization and segmentation methods.
Keyword Challenge
Intervertebral disc
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
School of Information Technology and Electrical Engineering Publications
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