Abstract
We present in this paper a novel interpretation of the concept of an “expert” in image segmentation as the pairing of an atlas image and a non-rigid registration algorithm. We introduce an extension to a recently presented expectation maximization (EM) algorithm for ground truth recovery, which allows us to integrate the segmentations obtained from multiple experts (i.e., from multiple atlases and/or using multiple image registration algorithms) and combine them into a final segmentation. In a validation study with randomly deformed segmentations we demonstrate the superiority of our method over simple label voting.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
BM Dawant, SL Hartmann, JP Thirion, F Maes, D Vandermeulen, P Demaerel. Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformations: Part I, methodology and validation on normal subjects. IEEE Trans Med Imag, 18(10):909–916, 1999.
T Rohlfing, R Brandt, CR Maurer, Jr, R Menzel. Bee brains, B-splines and computational democracy: Generating an average shape atlas. In IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, pp. 187–194, IEEE Computer Society, Los Alamitos, CA, 2001.
T Rohlfing, R Brandt, R Menzel, CR Maurer, Jr Segmentation of three-dimensional images using non-rigid registration: Methods and validation with application to confocal microscopy images of bee brains. In Medical Imaging: Image Processing, Proceedings of SPIE, 2003.
TW Sederberg, SR Parry. Free-form deformation and solid geometric models. Comput Graph (ACM), 20(4):151–160, 1986.
SK Warfield, KH Zou, WM Wells. Validation of image segmentation and expert quality with an expectation-maximization algorithm. In Proceedings of Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention, Part I, vol. vn2488 of LNCS, pp. 298–306, Springer-Verlag, Berlin, 2002.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rohlfing, T., Russakoff, D.B., Maurer, C.R. (2003). An Expectation Maximization-Like Algorithm for Multi-atlas Multi-label Segmentation. In: Wittenberg, T., Hastreiter, P., Hoppe, U., Handels, H., Horsch, A., Meinzer, HP. (eds) Bildverarbeitung für die Medizin 2003. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18993-7_71
Download citation
DOI: https://doi.org/10.1007/978-3-642-18993-7_71
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00619-0
Online ISBN: 978-3-642-18993-7
eBook Packages: Springer Book Archive