Corinna Blasse1, Stephan Saalfeld2, Raphaël Etournay1,3, Andreas Sagner1,4, Suzanne Eaton1, Eugene W Myers1,5. 1. Max Planck Institute of Molecular Cell Biology and Genetics, Dresden 01307, Germany. 2. Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA. 3. Department of Neuroscience, Institut Pasteur, Paris 75015, France. 4. The Francis Crick Institute, London NW1 1AT, UK. 5. Center for Systems Biology Dresden, Germany.
Abstract
MOTIVATION: A significant focus of biological research is to understand the development, organization and function of tissues. A particularly productive area of study is on single layer epithelial tissues in which the adherence junctions of cells form a 2D manifold that is fluorescently labeled. Given the size of the tissue, a microscope must collect a mosaic of overlapping 3D stacks encompassing the stained surface. Downstream interpretation is greatly simplified by preprocessing such a dataset as follows: (i) extracting and mapping the stained manifold in each stack into a single 2D projection plane, (ii) correcting uneven illumination artifacts, (iii) stitching the mosaic planes into a single, large 2D image and (iv) adjusting the contrast. RESULTS: We have developed PreMosa, an efficient, fully automatic pipeline to perform the four preprocessing tasks above resulting in a single 2D image of the stained manifold across which contrast is optimized and illumination is even. Notable features are as follows. First, the 2D projection step employs a specially developed algorithm that actually finds the manifold in the stack based on maximizing contrast, intensity and smoothness. Second, the projection step comes first, implying all subsequent tasks are more rapidly solved in 2D. And last, the mosaic melding employs an algorithm that globally adjusts contrasts amongst the 2D tiles so as to produce a seamless, high-contrast image. We conclude with an evaluation using ground-truth datasets and present results on datasets from Drosophila melanogaster wings and Schmidtae mediterranea ciliary components. AVAILABILITY AND IMPLEMENTATION: PreMosa is available under https://cblasse.github.io/premosa. CONTACT: blasse@mpi-cbg.de or myers@mpi-cbg.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: A significant focus of biological research is to understand the development, organization and function of tissues. A particularly productive area of study is on single layer epithelial tissues in which the adherence junctions of cells form a 2D manifold that is fluorescently labeled. Given the size of the tissue, a microscope must collect a mosaic of overlapping 3D stacks encompassing the stained surface. Downstream interpretation is greatly simplified by preprocessing such a dataset as follows: (i) extracting and mapping the stained manifold in each stack into a single 2D projection plane, (ii) correcting uneven illumination artifacts, (iii) stitching the mosaic planes into a single, large 2D image and (iv) adjusting the contrast. RESULTS: We have developed PreMosa, an efficient, fully automatic pipeline to perform the four preprocessing tasks above resulting in a single 2D image of the stained manifold across which contrast is optimized and illumination is even. Notable features are as follows. First, the 2D projection step employs a specially developed algorithm that actually finds the manifold in the stack based on maximizing contrast, intensity and smoothness. Second, the projection step comes first, implying all subsequent tasks are more rapidly solved in 2D. And last, the mosaic melding employs an algorithm that globally adjusts contrasts amongst the 2D tiles so as to produce a seamless, high-contrast image. We conclude with an evaluation using ground-truth datasets and present results on datasets from Drosophila melanogaster wings and Schmidtae mediterranea ciliary components. AVAILABILITY AND IMPLEMENTATION: PreMosa is available under https://cblasse.github.io/premosa. CONTACT: blasse@mpi-cbg.de or myers@mpi-cbg.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Marc Combalia; Sergio Garcia; Josep Malvehy; Susana Puig; Alba Guembe Mülberger; James Browning; Sandra Garcet; James G Krueger; Samantha R Lish; Rivka Lax; Jeannie Ren; Mary Stevenson; Nicole Doudican; John A Carucci; Manu Jain; Kevin White; Jaroslav Rakos; Daniel S Gareau Journal: Biomed Opt Express Date: 2021-05-05 Impact factor: 3.562