Mosaicing of Single Plane Illumination Microscopy Images Using Groupwise Registration and Fast Content-Based Image Fusion

Citation

Stephan Preibisch, Torsten Rohlfing, Michael P. Hasak, and Pavel Tomancak “Mosaicing of single plane illumination microscopy images using groupwise registration and fast content-based image fusion”, Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 69140E (26 March 2008); https://doi.org/10.1117/12.770893

Abstract

Single Plane Illumination Microscopy (SPIM; Huisken et al., Nature 305(5686):1007-1009, 2004) is an emerging microscopic technique that enables live imaging of large biological specimens in their entirety. By imaging the living biological sample from multiple angles SPIM has the potential to achieve isotropic resolution throughout even relatively large biological specimens. For every angle, however, only a relatively shallow section of the specimen is imaged with high resolution, whereas deeper regions appear increasingly blurred. In order to produce a single, uniformly high resolution image, we propose here an image mosaicing algorithm that combines state of the art groupwise image registration for alignment with content-based image fusion to prevent degrading of the fused image due to regional blurring of the input images. For the registration stage, we introduce an application-specific groupwise transformation model that incorporates per-image as well as groupwise transformation parameters. We also propose a new fusion algorithm based on Gaussian filters, which is substantially faster than fusion based on local image entropy. We demonstrate the performance of our mosaicing method on data acquired from living embryos of the fruit fly, Drosophila, using four and eight angle acquisitions.


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