The genome is partitioned into regions of euchromatin and heterochromatin. The organization of heterochromatin is important for the regulation of cellular processes such as chromosome segregation and gene silencing, a...
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The genome is partitioned into regions of euchromatin and heterochromatin. The organization of heterochromatin is important for the regulation of cellular processes such as chromosome segregation and gene silencing, and their misregulation is linked to cancer and other diseases. We present a model-based approach for automatic 3d segmentation and3d shape analysis of heterochromatin foci from 3d con focal light microscopy images. Our approach employs a novel 3dintensitymodel based on spherical harmonics, which analytically describes the shape and intensities of the foci. The model parameters are determined by fitting the model to the image intensities using least-squares minimization. To characterize the 3d shape of the foci, we exploit the computed spherical harmonics coefficients anddetermine a shape descriptor. We applied our approach to 3d synthetic image data as well as real 3d static and real 3d time-lapse microscopy images, and compared the performance with that of previous approaches. It turned out that our approach yields accurate 3d segmentation results and performs better than previous approaches. We also show that our approach can be used for quantifying 3d shape differences of heterochromatin foci. (C) 2016 Elsevier B.V. All rights reserved.
We introduce a 3dmodel-based approach for automatic segmentation of 3d fluorescent heterochromatin foci from microscopy images. The approach employs a new 3d parametric intensity model based on a spherical harmonics ...
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ISBN:
(纸本)9781467364553
We introduce a 3dmodel-based approach for automatic segmentation of 3d fluorescent heterochromatin foci from microscopy images. The approach employs a new 3d parametric intensity model based on a spherical harmonics (SH) expansion and can represent foci of regular and highly irregular shapes. By solving a least-squares minimization problem, the new model is directly fitted to the 3d image data, and the model parameters including the SH expansion coefficients are estimated. The approach has been successfully applied to real 3d microscopy image data and has been compared to previous approaches.
We introduce an adaptive model fitting approach for the segmentation of vessels from 3d tomographic images. With this approach the shape and size of the 3d region-of-interest (ROI) used for model fitting are automatic...
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ISBN:
(纸本)9780819466297
We introduce an adaptive model fitting approach for the segmentation of vessels from 3d tomographic images. With this approach the shape and size of the 3d region-of-interest (ROI) used for model fitting are automatically adapted to the local width, curvature, and orientation of a vessel to increase the robustness and accuracy. The approach uses a 3d cylindrical model and has been successfully applied to segment human vessels from 3d MRA image data. Our experiments show that the new adaptive scheme yields superior segmentation results in comparison to using a fixed size ROI. Moreover, a validation of the approach based on ground-truth provided by a radiologist confirms its accuracy. In addition, we also performed an experimental comparison of the new approach with a previous scheme.
We introduce a new model-based approach for segmenting and quantifying fluorescent bacteria in 3d microscopy live cell images. The approach is based on a new 3d superellipsoidal parametricintensitymodel, which is di...
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ISBN:
(纸本)9780819466303
We introduce a new model-based approach for segmenting and quantifying fluorescent bacteria in 3d microscopy live cell images. The approach is based on a new 3d superellipsoidal parametricintensitymodel, which is directly fitted to the image intensities within 3d regions-of-interest. Based on the fitting results, we can directly compute the total amount of intensity (fluorescence) of each cell. In addition, we introduce a method for automatic initialization of the model parameters, and we propose a method for simultaneously fitting clustered cells by using a superposition of 3d superellipsoids for model fitting. We demonstrate the applicability of our approach based on 3d synthetic and real 3d microscopy images.
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