Quantification of spinal cord atrophy from magnetic resonance images via a B‐spline active surface model

A method is presented that aims at segmenting and measuring the surface of the spinal cord from MR images in order to detect and quantify atrophy. A semiautomatic segmentation with very little intervention from an operator is proposed. It is based on the optimization of a B‐spline active surface. The method allows for the computation of orthogonal cross‐sections at any level along the cord, from which measurements are derived, such as cross‐sectional area or curvature. An evaluation of the accuracy and reproducibility of the method is presented. Magn Reson Med 47:1176–1185, 2002. © 2002 Wiley‐Liss, Inc.

[1]  Gareth J. Barker,et al.  Cervical spinal cord volume estimation using an active surface method: a amgnetic resonance imaging study in multiple sclerosis , 2001 .

[2]  A. Thompson,et al.  Spinal cord MRI using multi‐array coils and fast spin echo , 1993, Neurology.

[3]  G. T. Plant,et al.  Detection of optic nerve atrophy following a single episode of unilateral optic neuritis by MRI using a fat-saturated short-echo fast FLAIR sequence , 2001, Neuroradiology.

[4]  Demetri Terzopoulos,et al.  Deformable models in medical image analysis: a survey , 1996, Medical Image Anal..

[5]  B. Morse Computation of object cores from grey-level images , 1996 .

[6]  H. Piaggio Differential Geometry of Curves and Surfaces , 1952, Nature.

[7]  A. Thompson,et al.  Spinal cord MRI using multi‐array coils and fast spin echo , 1993, Neurology.

[8]  S J Hickman,et al.  Imaging of the spine in multiple sclerosis. , 2000, Neuroimaging clinics of North America.

[9]  A. Thompson,et al.  Spinal cord atrophy and disability in multiple sclerosis. A new reproducible and sensitive MRI method with potential to monitor disease progression. , 1996, Brain : a journal of neurology.

[10]  Amir A. Amini,et al.  Snakes and Splines for Tracking Non-Rigid Heart Motion , 1996, ECCV.

[11]  Mubarak Shah,et al.  A Fast algorithm for active contours and curvature estimation , 1992, CVGIP Image Underst..

[12]  Gerard Medioni,et al.  Representation of range data with B-spline surface patches , 1992, Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol. III. Conference C: Image, Speech and Signal Analysis,.

[13]  S. Medendorp,et al.  Magnetic resonance imaging lesion enlargement in multiple sclerosis. Disease-related activity, chance occurrence, or measurement artifact? , 1992, Archives of neurology.

[14]  Manfredo P. do Carmo,et al.  Differential geometry of curves and surfaces , 1976 .

[15]  Massimo Filippi,et al.  A spinal cord MRI study of benign and secondary progressive multiple sclerosis , 2004, Journal of Neurology.

[16]  Amir A. Amini,et al.  Quantitative coronary angiography with deformable spline models , 1997, IEEE Transactions on Medical Imaging.

[17]  James S. Duncan,et al.  Bending and stretching models for LV wall motion analysis from curves and surfaces , 1992, Image Vis. Comput..

[18]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[19]  N. Losseff,et al.  Measures of brain and spinal cord atrophy in multiple sclerosis. , 1998, Journal of neurology, neurosurgery, and psychiatry.

[20]  Guillermo Sapiro,et al.  Geodesic Active Contours , 1995, International Journal of Computer Vision.

[21]  Hickman Sj,et al.  Imaging of the spine in multiple sclerosis. , 2000 .

[22]  Massimo Filippi,et al.  Assessment of spinal cord damage in MS using MRI , 2000, Journal of the Neurological Sciences.

[23]  Simon R. Arridge,et al.  Active shape focusing , 1999, Image Vis. Comput..