Spinal Cord Segmentation by One Dimensional Normalized Template Matching: A Novel, Quantitative Technique to Analyze Advanced Magnetic Resonance Imaging Data

被引:7
作者
Cadotte, Adam [1 ]
Cadotte, David W. [1 ,2 ]
Livne, Micha [3 ]
Cohen-Adad, Julien [4 ,5 ]
Fleet, David [3 ]
Mikulis, David [2 ,6 ]
Fehlings, Michael G. [1 ,2 ,7 ]
机构
[1] Univ Toronto, Dept Surg, Div Neurosurg, Toronto, ON, Canada
[2] Toronto Western Hosp, Univ Hlth Network, Toronto, ON M5T 2S8, Canada
[3] Univ Toronto, Dept Comp Sci, Toronto, ON, Canada
[4] Ecole Polytech, Inst Biomed Engn, Montreal, PQ H3C 3A7, Canada
[5] Univ Montreal, Funct Neuroimaging Unit, CRIUGM, Montreal, PQ, Canada
[6] Univ Toronto, Dept Med Imaging, Div Neuroradiol, Toronto, ON, Canada
[7] Univ Toronto, Spine Program, Toronto, ON, Canada
关键词
AUTOMATIC SEGMENTATION; IMAGES; ATROPHY;
D O I
10.1371/journal.pone.0139323
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
070301 [无机化学]; 070403 [天体物理学]; 070507 [自然资源与国土空间规划学]; 090105 [作物生产系统与生态工程];
摘要
Spinal cord segmentation is a developing area of research intended to aid the processing and interpretation of advanced magnetic resonance imaging (MRI). For example, high resolution three-dimensional volumes can be segmented to provide a measurement of spinal cord atrophy. Spinal cord segmentation is difficult due to the variety of MRI contrasts and the variation in human anatomy. In this study we propose a new method of spinal cord segmentation based on one-dimensional template matching and provide several metrics that can be used to compare with other segmentation methods. A set of ground-truth data from 10 subjects was manually-segmented by two different raters. These ground truth data formed the basis of the segmentation algorithm. A user was required to manually initialize the spinal cord center-line on new images, taking less than one minute. Template matching was used to segment the new cord and a refined center line was calculated based on multiple centroids within the segmentation. Arc distances down the spinal cord and cross-sectional areas were calculated. Inter-rater validation was performed by comparing two manual raters (n = 10). Semi-automatic validation was performed by comparing the two manual raters to the semi-automatic method (n = 10). Comparing the semi-automatic method to one of the raters yielded a Dice coefficient of 0.91 +/- 0.02 for ten subjects, a mean distance between spinal cord center lines of 0.32 +/- 0.08 mm, and a Hausdorff distance of 1.82 +/- 0.33 mm. The absolute variation in cross-sectional area was comparable for the semi-automatic method versus manual segmentation when compared to inter-rater manual segmentation. The results demonstrate that this novel segmentation method performs as well as a manual rater for most segmentation metrics. It offers a new approach to study spinal cord disease and to quantitatively track changes within the spinal cord in an individual case and across cohorts of subjects.
引用
收藏
页数:18
相关论文
共 14 条
[1]
Groupwise multi-atlas segmentation of the spinal cord's internal structure [J].
Asman, Andrew J. ;
Bryan, Frederick W. ;
Smith, Seth A. ;
Reich, Daniel S. ;
Landman, Bennett A. .
MEDICAL IMAGE ANALYSIS, 2014, 18 (03) :460-471
[2]
Mesh: Measuring errors between surfaces using the Hausdorff distance [J].
Aspert, N ;
Santa-Cruz, D ;
Ebrahimi, T .
IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, VOL I AND II, PROCEEDINGS, 2002, :705-708
[3]
Cadotte DW, 2014, AM J NEURORADIOLOGY
[4]
Automatic magnetic resonance spinal cord segmentation with topology constraints for variable fields of view [J].
Chen, Min ;
Carass, Aaron ;
Oh, Jiwon ;
Nair, Govind ;
Pham, Dzung L. ;
Reich, Daniel S. ;
Prince, Jerry L. .
NEUROIMAGE, 2013, 83 :1051-1062
[5]
Demyelination and degeneration in the injured human spinal cord detected with diffusion and magnetization transfer MRI [J].
Cohen-Adad, J. ;
El Mendili, M-M. ;
Lehericy, S. ;
Pradat, P-F. ;
Blancho, S. ;
Rossignol, S. ;
Benali, H. .
NEUROIMAGE, 2011, 55 (03) :1024-1033
[6]
Quantification of spinal cord atrophy from magnetic resonance images via a B-spline active surface model [J].
Coulon, O ;
Hickman, SJ ;
Parker, GJ ;
Barker, GJ ;
Miller, DH ;
Arridge, SR .
MAGNETIC RESONANCE IN MEDICINE, 2002, 47 (06) :1176-1185
[7]
Robust, accurate and fast automatic segmentation of the spinal cord [J].
De Leener, Benjamin ;
Kadoury, Samuel ;
Cohen-Adad, Julien .
NEUROIMAGE, 2014, 98 :528-536
[8]
MEASURES OF THE AMOUNT OF ECOLOGIC ASSOCIATION BETWEEN SPECIES [J].
DICE, LR .
ECOLOGY, 1945, 26 (03) :297-302
[9]
Rapid semi-automatic segmentation of the spinal cord from magnetic resonance images: Application in multiple sclerosis [J].
Horsfield, Mark A. ;
Sala, Stefania ;
Neema, Mohit ;
Absinta, Martina ;
Bakshi, Anshika ;
Sormani, Maria Pia ;
Rocca, Maria A. ;
Bakshi, Rohit ;
Filippi, Massimo .
NEUROIMAGE, 2010, 50 (02) :446-455
[10]
Koh J, 2011, I S BIOMED IMAGING, P1467, DOI 10.1109/ISBI.2011.5872677