15 March 2011 Reconstruction of high-resolution fluorescence microscopy images based on axial tomography
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Proceedings Volume 7962, Medical Imaging 2011: Image Processing; 79624O (2011) https://doi.org/10.1117/12.878260
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States
For a reliable understanding of cellular processes, high resolution 3D images of the investigated cells are necessary. Unfortunately, the ability of fluorescence microscopes to image a cell in 3D is limited since the resolution along the optical axis is by a factor of two to three worse than the transversal resolution. Standard microscopy image deblurring algorithms like the Total Variation regularized Richardson Lucy algorithm are able to improve the resolution but the problem of a lower resolution in direction along the optical axis remains. However, it is possible to overcome this problem using Axial Tomography providing tilted views of the object by rotating it under the microscope. The rotated images contain additional information about the objects and an advanced method to reconstruct a 3D image with an isotropic resolution is presented here. First, bleaching has to be corrected in order to allow a valid registration correcting translational and rotational shifts. Hereby, a multi-resolution rigid registration method is used in our method. A single high-resolution image can be reconstructed on basis of all aligned images using an extended Richardson Lucy method. In addition, a Total Variation regularization is applied in order to guarantee a stable reconstruction result. The results for both simulated and real data show a considerable improvement of the resolution in direction of the optical axis.
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Steffen Remmele, Steffen Remmele, Bianca Oehm, Bianca Oehm, Florian Staier, Florian Staier, Heinz Eipel, Heinz Eipel, Christoph Cremer, Christoph Cremer, Jürgen Hesser, Jürgen Hesser, } "Reconstruction of high-resolution fluorescence microscopy images based on axial tomography", Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 79624O (15 March 2011); doi: 10.1117/12.878260; https://doi.org/10.1117/12.878260

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