Toward a clinical lumbar CAD: herniation diagnosis

被引:36
作者
Alomari, Raja' S. [1 ]
Corso, Jason J. [1 ]
Chaudhary, Vipin [1 ]
Dhillon, Gurmeet [2 ]
机构
[1] SUNY Buffalo, Dept Comp Sci & Engn, Buffalo, NY 14260 USA
[2] ProScan Imaging Buffalo, Williamsville, NY 14221 USA
基金
美国国家科学基金会;
关键词
Lumbar spine; Clinical MRI; CAD; GVF-snake; Active contour; Gibbs distribution; Bayes model; DISC; DEGENERATION;
D O I
10.1007/s11548-010-0487-7
中图分类号
R318 [生物医学工程];
学科分类号
100103 [病原生物学];
摘要
Purpose A CAD system for lumbar disc degeneration and herniation based on clinical MR images can aid diagnostic decision-making provided the method is robust, efficient, and accurate. Material and methods A Bayesian-based classifier with a Gibbs distribution was designed and implemented for diagnosing lumbar disc herniation. Each disc is segmented with a gradient vector flow active contour model (GVF-snake) to extract shape features that feed a classifier. The GVF-snake is automatically initialized with an inner boundary of the disc initiated by a point inside the disc. This point is automatically generated by our previous work on lumbar disc labeling. The classifier operates on clinical T2-SPIR weighted sagittal MRI of the lumbar area. The classifier is applied slice-by-slice to tag herniated discs if they are classified as herniated in any of the 2D slices. This technique detects all visible herniated discs regardless of their location (lateral or central). The gold standard for the ground truth was obtained from collaborating radiologists by analyzing the clinical diagnosis report for each case. Results An average 92.5% herniation diagnosis accuracy was observed in a cross-validation experiment with 65 clinical cases. The random leave-out experiment runs ten rounds; in each round, 35 cases were used for testing and the remaining 30 cases were used for training. Conclusion An automatic robust disk herniation diagnostic method for clinical lumbar MRI was developed and tested. The method is intended for clinical practice to support reliable decision-making.
引用
收藏
页码:119 / 126
页数:8
相关论文
共 23 条
[1]
Introduction - Disc degeneration: Summary [J].
An, HS ;
Anderson, PA ;
Haughton, VM ;
Iatridis, JC ;
Kang, JD ;
Lotz, JC ;
Natarajan, RN ;
Oegema, TR ;
Roughley, P ;
Setton, LA ;
Urban, JP ;
Videman, T ;
Andersson, GBJ ;
Weinstein, JN .
SPINE, 2004, 29 (23) :2677-2678
[2]
[Anonymous], P IEEE INT C NEURAL
[3]
Corso JJ, 2008, LECT NOTES COMPUT SC, V5241, P202, DOI 10.1007/978-3-540-85988-8_25
[4]
DAVID FF, 2001, NOMENCLATURE CLASSIF
[5]
Nomenclature and classification of lumbar disc pathology [J].
Fardon, DF .
SPINE, 2001, 26 (05) :461-462
[6]
*ICAD, 2009, SPECTR LOOK DIG IC C
[7]
*ICAD, 2009, VIV LOOK IC COMP AID
[8]
Liver segmentation for CT images using GVF snake [J].
Liu, F ;
Zhao, BS ;
Kijewski, PK ;
Wang, L ;
Schwartz, LH .
MEDICAL PHYSICS, 2005, 32 (12) :3699-3706
[9]
Atlas-Based Segmentation of Degenerated Lumbar Intervertebral Discs From MR Images of the Spine [J].
Michopoulou, Sofia K. ;
Costaridou, Lena ;
Panagiotopoulos, Elias ;
Speller, Robert ;
Panayiotakis, George ;
Todd-Pokropek, Andrew .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2009, 56 (09) :2225-2231
[10]
Mulconrey Daniel S, 2006, Spine J, V6, P177, DOI 10.1016/j.spinee.2005.08.011