Seamless stitching of tile scan microscope images

For diagnostic purposes, optical imaging techniques need to obtain high‐resolution images of extended biological specimens in reasonable time. The field of view of an objective lens, however, is often smaller than the sample size. To image the whole sample, laser scanning microscopes acquire tile scans that are stitched into larger mosaics. The appearance of such image mosaics is affected by visible edge artefacts that arise from various optical aberrations which manifest in grey level jumps across tile boundaries. In this contribution, a technique for stitching tiles into a seamless mosaic is presented. The stitching algorithm operates by equilibrating neighbouring edges and forcing the brightness at corners to a common value. The corrected image mosaics appear to be free from stitching artefacts and are, therefore, suited for further image analysis procedures. The contribution presents a novel method to seamlessly stitch tiles captured by a laser scanning microscope into a large mosaic. The motivation for the work is the failure of currently existing methods for stitching nonlinear, multimodal images captured by our microscopic setups. Our method eliminates the visible edge artefacts that appear between neighbouring tiles by taking into account the overall illumination differences among tiles in such mosaics. The algorithm first corrects the nonuniform brightness that exists within each of the tiles. It then compensates for grey level differences across tile boundaries by equilibrating neighbouring edges and forcing the brightness at the corners to a common value. After these artefacts have been removed further image analysis procedures can be applied on the microscopic images. Even though the solution presented here is tailored for the aforementioned specific case, it could be easily adapted to other contexts where image tiles are assembled into mosaics such as in astronomical or satellite photos.

[1]  Patrick Pérez,et al.  Poisson image editing , 2003, ACM Trans. Graph..

[2]  Kevin W Eliceiri,et al.  NIH Image to ImageJ: 25 years of image analysis , 2012, Nature Methods.

[3]  Edward H. Adelson,et al.  A multiresolution spline with application to image mosaics , 1983, TOGS.

[4]  D. Shepard A two-dimensional interpolation function for irregularly-spaced data , 1968, ACM National Conference.

[5]  David Salesin,et al.  Interactive digital photomontage , 2004, ACM Trans. Graph..

[6]  C. D. Kuglin,et al.  The phase correlation image alignment method , 1975 .

[7]  Gengfeng Zheng,et al.  Laser-scanning coherent anti-Stokes Raman scattering microscopy and applications to cell biology. , 2002, Biophysical journal.

[8]  Jens Limpert,et al.  Expanding multimodal microscopy by high spectral resolution coherent anti-Stokes Raman scattering imaging for clinical disease diagnostics. , 2013, Analytical chemistry.

[9]  X. Xie,et al.  Nonperturbative chemical imaging of organelle transport in living cells with coherent anti-stokes Raman scattering microscopy. , 2006, Biophysical journal.

[10]  Alessandro Bevilacqua,et al.  Quantitative Quality Assessment of Microscopic Image Mosaicing , 2010 .

[11]  Michael Unser,et al.  User‐friendly semiautomated assembly of accurate image mosaics in microscopy , 2007, Microscopy research and technique.

[12]  Christian Matthäus,et al.  A compact microscope setup for multimodal nonlinear imaging in clinics and its application to disease diagnostics. , 2013, The Analyst.

[13]  Matthew A. Brown,et al.  Automatic Panoramic Image Stitching using Invariant Features , 2007, International Journal of Computer Vision.

[14]  Abraham J. Koster,et al.  Virtual nanoscopy: Generation of ultra-large high resolution electron microscopy maps , 2012, The Journal of cell biology.

[15]  Reinhard Klette,et al.  Image Stitching - Comparisons and New Techniques , 1999, CAIP.

[16]  Stephan Saalfeld,et al.  Globally optimal stitching of tiled 3D microscopic image acquisitions , 2009, Bioinform..

[17]  Richard Szeliski,et al.  Eliminating ghosting and exposure artifacts in image mosaics , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.