2011
DOI: 10.1109/tip.2010.2076377
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Nonrigid Registration of 2-D and 3-D Dynamic Cell Nuclei Images for Improved Classification of Subcellular Particle Motion

Abstract: The observed motion of subcellular particles in fluorescence microscopy image sequences of live cells is generally a superposition of the motion and deformation of the cell and the motion of the particles. Decoupling the two types of movements to enable accurate classification of the particle motion requires the application of registration algorithms. We have developed an intensity-based approach for nonrigid registration of multi-channel microscopy image sequences of cell nuclei. First, based on 3-D synthetic… Show more

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Cited by 33 publications
(37 citation statements)
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“…However tracking methods are not always adapted for motion analysis, especially when the density and the lack of prominent features prevent the individual extraction of objects of interest undergoing complex motion. Accordingly, estimating motion fields can be then more appropriate to capture complex dynamics observed in biological sequences [247], [248]. The usual approach for optical flow estimates the dense motion field by minimizing a global energy functional composed of two terms: (7) where is the dense motion field, is a data term penalizing deviations from a data conservation assumption over time, is a regularization term enforcing smoothness of the flow field and serves as regularization parameter to balance and contributions.…”
Section: Discussion and Comparisonmentioning
confidence: 99%
“…However tracking methods are not always adapted for motion analysis, especially when the density and the lack of prominent features prevent the individual extraction of objects of interest undergoing complex motion. Accordingly, estimating motion fields can be then more appropriate to capture complex dynamics observed in biological sequences [247], [248]. The usual approach for optical flow estimates the dense motion field by minimizing a global energy functional composed of two terms: (7) where is the dense motion field, is a data term penalizing deviations from a data conservation assumption over time, is a regularization term enforcing smoothness of the flow field and serves as regularization parameter to balance and contributions.…”
Section: Discussion and Comparisonmentioning
confidence: 99%
“…Many conceptual and methodological links can also be found between medical image registration and optical flow [100,211,212,219,224]. In microscopy, dense motion can inform about cell deformation [3,90,139,203], motion of cellular structures [73,89], or help for individual cell tracking [167].…”
Section: Applicative Domainsmentioning
confidence: 99%
“…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.…”
Section: Introductionmentioning
confidence: 99%
“…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.…”
Section: Introductionmentioning
confidence: 99%