Bone MRI segmentation assessment based on synchrotron radiation computed microtomography

In this paper, we propose an original scheme to assess the efficiency of segmentation algorithms requested to quantify bone architecture from 3D micro MRI techniques. Our scheme takes advantage of the high quality images provided by Synchrotron Radiation Computed MicroTomography (SR /spl mu/CT). To perform this assessment, calcaneus samples were acquired both from SR /spl mu/CT and MRI devices. The segmentation process is evaluated by comparing morphometric and topologic parameters computed from the SR /spl mu/CT reference images and those computed from the MRI segmented images. Both an adaptive thresholding algorithm and a region growing algorithm are tested within this framework.

[1]  Rolf Adams,et al.  Seeded Region Growing , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Françoise Peyrin,et al.  Automated 3D region growing algorithm governed by an evaluation function , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[3]  M. Hahn,et al.  High Spatial Resolution Imaging of Bone Mineral Using Computed Microtomography: Comparison with Microradiography and Undecalcified Histologic Sections , 1993, Investigative radiology.

[4]  S. Majumdar,et al.  High-resolution magnetic resonance imaging: three-dimensional trabecular bone architecture and biomechanical properties. , 1998, Bone.

[5]  P Cloetens,et al.  A synchrotron radiation microtomography system for the analysis of trabecular bone samples. , 1999, Medical physics.

[6]  F. Wehrli,et al.  Three‐dimensional nuclear magnetic resonance microimaging of trabecular bone , 1995, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[7]  Theocharis Antoniadis,et al.  Bone labelling on micro-magnetic resonance images , 1999, Medical Image Anal..

[8]  Michel Jourlin,et al.  A new minimum variance region growing algorithm for image segmentation , 1997, Pattern Recognit. Lett..

[9]  C. Simmons,et al.  Method‐Based Differences in the Automated Analysis of the Three‐Dimensional Morphology of Trabecular Bone , 1997, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[10]  N. Otsu A threshold selection method from gray level histograms , 1979 .

[11]  H. Gundersen,et al.  Quantification of connectivity in cancellous bone, with special emphasis on 3-D reconstructions. , 1993, Bone.