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

Autor: Jurgen Fripp, Martin Urschler, Maria Wimmer, Hao Chen, Hui Cheng, Shuo Li, Chunliang Wang, Robert Korez, Daniel Forsberg, Dieter Felsenberg, Gabriele Armbrecht, Tomaž Vrtovec, Darko Štern, Pheng-Ann Heng, Isabel Lŏpez Andrade, Alexey A. Novikov, Qi Dou, Hugo Hutt, Richard M. Everson, Bulat Ibragimov, Ben Glocker, Guoyan Zheng, Daniel L. Belavý, Ales Neubert, Chengwen Chu, Judith R. Meakin
Rok vydání: 2017
Předmět:
Reference data (financial markets)
Health Informatics
02 engineering and technology
030218 nuclear medicine & medical imaging
03 medical and health sciences
Imaging
Three-Dimensional
0302 clinical medicine
0202 electrical engineering
electronic engineering
information engineering
medicine
Humans
Radiology
Nuclear Medicine and imaging
Segmentation
Computer vision
Intervertebral Disc
610 Medicine & health
Radiological and Ultrasound Technology
medicine.diagnostic_test
business.industry
Medical image computing
Intervertebral disc
Magnetic resonance imaging
620 Engineering
Magnetic Resonance Imaging
Computer Graphics and Computer-Aided Design
Hausdorff distance
medicine.anatomical_structure
570 Life sciences
biology
020201 artificial intelligence & image processing
Computer Vision and Pattern Recognition
Artificial intelligence
Mr images
business
Algorithms
Zdroj: Medical Image Analysis. 35:327-344
ISSN: 1361-8415
DOI: 10.1016/j.media.2016.08.005
Popis: 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.
Databáze: OpenAIRE
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