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Anisotropic plate diffusion filtering for detection of cell membranes in 3D microscopy images

机译:各向异性板扩散过滤在3D显微镜图像中检测细胞膜

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We propose an anisotropic diffusion method to denoise and aid the reconstruction of planar objects in three-dimensional images. The contribution of this paper is the development of a planarity function characterizing plate-like structures using an image Hessian's eigensystem. We then construct a diffusion tensor for anisotropically smoothing plates and satisfying necessary scale-space properties. Our method finds applications in improving the fidelity of highly noisy cell membrane images from confocal microscopy. In dense cellular regions, cell membranes assume linear shapes (planar) between neighbors. The imaging process makes cell membranes appear as diffuse structures owing to the non-uniform fluorescent marker distribution, point-spread function of the optics, and anisotropic voxel resolution which make automatic cell segmentation difficult. We apply diffusion filtering to identify and enhance membranes. We demonstrate the use of our methods on 3D cell membrane images of a zebrafish embryo acquired using fluorescent microscopy and quantify the improvement in image quality.
机译:我们提出了一种各向异性扩散方法来对三维图像中的平面物体进行降噪和辅助重建。本文的贡献是利用图像Hessian本征系统开发了表征板状结构的平面度函数。然后,我们为各向异性平滑板构造一个扩散张量,并满足必要的尺度空间性质。我们的方法在提高共聚焦显微镜中高噪声细胞膜图像的保真度方面有应用。在密集的细胞区域中,细胞膜在邻居之间呈线性形状(平面)。由于不均匀的荧光标记分布,光学元件的点扩展功能以及各向异性体素分辨率,使得细胞膜难以自动分割,因此成像过程使细胞膜呈现为扩散结构。我们应用扩散过滤来识别和增强膜。我们证明了我们的方法在使用荧光显微镜获得的斑马鱼胚胎的3D细胞膜图像上的使用,并量化了图像质量的提高。

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