Nonrigid Registration of 3-D Multichannel Microscopy Images of Cell Nuclei

Abstract

We present an intensity-based nonrigid registration approach for the normalization of 3-D multichannel 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 from the cell nucleus channel, smooth the resulting images by a Gaussian filter, and then apply an intensity-based registration algorithm. The obtained transformation is applied to the images from the nucleus channel as well as to the images from the other channels. To improve the convergence rate of the algorithm, we propose an adaptive step length optimization scheme and also employ a multiresolution scheme. Our approach has been successfully applied using 2-D cell-like synthetic images, 3-D phantom images as well as 3-D multichannel microscopy images representing different chromosome territories and gene regions. We also describe an extension of our approach, which is applied for the registration of 3D + t (4-D) image series of moving cell nuclei.

Non-rigid multi-frame registration of live cell microscopy images

“…where T (x, u) denotes the transformation using the vector field u, x is the spatial coordinate, g k (T (x, u)) is the image at time point k warped with u, and g l (T (x, u(g l , g k−1 ))) is the image at time point l warped using (2). A diagram of the multi-frame consecutive registration approach is shown in Fig.…”

“…The weighting approach has been previously used for pairwise registration of microscopy images and it performed better than other optic flow based registration approaches, e.g., symmetric Demons [2] and Lucas-Kanade [3,6]. The pairwise weighting approach is based on the optimization method of Levenberg-Marquardt and minimizes for each image point the squared intensity differences between pairs of successive images.…”

“…Mattes et al [1], for example, described a landmark-based registration approach for cell nuclei using thin-plate splines. Yang et al [2] used an extension of the Demons algorithm based on symmetric forces to register images of different cells as well as live cell microscopy images. Kim et al [3] introduced an extension of the Lucas-Kanade optic flow algorithm for the registration of dynamic cell nuclei images.…”

Four Dimensional Image Registration for Intravital Microscopy

“…A non-rigid registration method that utilizes multichannel temporal 2D and 3D microscopy images of cell nuclei to address global rigid and local non-rigid motion artifacts of cell nuclei is described in [15]. Another rigid registration method for canceling motion artifacts of biological objects based on frequency domain techniques is described in [16].…”

“…Yet another non-rigid registration method [17] that cancels motion artifacts of subcellular particles in live cell nuclei in temporal 2D and 3D microscopy images by using the extensions of an optic flow method. However, these techniques [15,16,17] are mainly used to register images that contain single cellular structure. An thin plate spline non-rigid registration method that registers images containing many live cells is described in [18], but it can only cancel the motion artifacts between successive z stack images.…”