Multi-atlas-based fully automatic segmentation of individual muscles in rat leg.

Objective: To quantify individual muscle volume in rat leg MR images using a fully automatic multi-atlas-based segmentation method.

Materials And Methods: We optimized a multi-atlas-based segmentation method to take into account the voxel anisotropy of numbers of MRI acquisition protocols. We mainly tested an image upsampling process along Z and a constraint on the nonlinear deformation in the XY plane. We also evaluated a weighted vote procedure and an original implementation of an artificial atlas addition. Using this approach, we measured gastrocnemius and plantaris muscle volumes and compared the results with manual segmentation. The method reliability for volume quantification was evaluated using the relative overlap index.

Results: The most accurate segmentation was obtained using a nonlinear registration constrained in the XY plane by zeroing the Z component of the displacement and a weighted vote procedure for both muscles regardless of the number of atlases. The performance of the automatic segmentation and the corresponding volume quantification outperformed the interoperator variability using a minimum of three original atlases.

Conclusion: We demonstrated the reliability of a multi-atlas segmentation approach for the automatic segmentation and volume quantification of individual muscles in rat leg and found that constraining the registration in plane significantly improved the results.