PreMosa: Extracting 2D surfaces from 3D microscopy mosaics
| Autor: | Raphaël Etournay, Corinna Blasse, Suzanne Eaton, Eugene W. Myers, Stephan Saalfeld, Andreas Sagner |
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| Přispěvatelé: | Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG), Max-Planck-Gesellschaft, Janelia Farm Research Campus, Howard Hughes Medical Institute (HHMI), Département de Neuroscience - Department of Neuroscience, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), The Francis Crick Institute [London], Center for Systems Biology Dresden (CSBD), Technische Universität Dresden = Dresden University of Technology (TU Dresden)-Max Planck Society, C.B. was supported by the German Federal Ministry of Research and Education (BMBF) under the funding code 031A099., Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Statistics and Probability Computer science Image processing 02 engineering and technology [SDV.BC]Life Sciences [q-bio]/Cellular Biology Biochemistry law.invention Image stitching 03 medical and health sciences Imaging Three-Dimensional law 0202 electrical engineering electronic engineering information engineering Image Processing Computer-Assisted Animals Wings Animal Computer vision Projection plane Cilia Projection (set theory) Molecular Biology Microscopy business.industry Pipeline (software) [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM] Manifold Computer Science Applications Computational Mathematics 030104 developmental biology Drosophila melanogaster Computational Theory and Mathematics Platyhelminths 020201 artificial intelligence & image processing Artificial intelligence Focus (optics) business Artifacts Manifold (fluid mechanics) Algorithms Software |
| Zdroj: | Bioinformatics Bioinformatics, Oxford University Press (OUP), 2017, pp.Bioinformatics btx195. ⟨10.1093/bioinformatics/btx195⟩ Bioinformatics, 2017, pp.Bioinformatics btx195. ⟨10.1093/bioinformatics/btx195⟩ |
| ISSN: | 1367-4803 1367-4811 |
| Popis: | 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 Supplementary information Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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