Non-rigid registration of 3d multi-channel microscopy images of cell nuclei

Authors:
Siwei Yang;Daniela Köhler;Kathrin Teller;Thomas Cremer;Patricia Le Baccon;Edith Heard;Roland Eils;Karl Rohr
Affiliations:
Biomedical Computer Vision Group, Dept. Theoretical Bioinformatics, DKFZ Heidelberg;Dept. of Biology II, Anthropology and Human Genetics, Ludwig Maximilians University Munich, Biozentrum, Germany;Dept. of Biology II, Anthropology and Human Genetics, Ludwig Maximilians University Munich, Biozentrum, Germany;Dept. of Biology II, Anthropology and Human Genetics, Ludwig Maximilians University Munich, Biozentrum, Germany;CNRS UMR 218, Curie Institute, Paris, France;CNRS UMR 218, Curie Institute, Paris, France;Biomedical Computer Vision Group, Dept. Theoretical Bioinformatics, DKFZ Heidelberg;Biomedical Computer Vision Group, Dept. Theoretical Bioinformatics, DKFZ Heidelberg
Venue:
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Year:
2006

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Abstract

We present an intensity-based non-rigid registration approach for normalizing 3D multi-channel microscopy images of cell nuclei. A main problem with cell nuclei images is that the intensity structure of different nuclei differs very much, thus an intensity-based registration scheme cannot be used directly. Instead, we first perform a segmentation of the images, smooth them by a Gaussian filter, and then apply an intensity-based algorithm. To improve the convergence rate of the algorithm, we propose an adaptive step length optimization scheme and also employ a multi-resolution scheme. Our approach has been successfully applied using 2D cell-like synthetic images, 3D phantom images as well as 3D multi-channel microscopy images representing different chromosome territories and gene regions (BACs). We also describe an extension of our approach which is applied for the registration of 3D+t (4D) image series of moving cell nuclei.