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      R 2OBBIE-3D, a Fast Robotic High-Resolution System for Quantitative Phenotyping of Surface Geometry and Colour-Texture

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          Abstract

          While recent imaging techniques provide insights into biological processes from the molecular to the cellular scale, phenotypes at larger scales remain poorly amenable to quantitative analyses. For example, investigations of the biophysical mechanisms generating skin morphological complexity and diversity would greatly benefit from 3D geometry and colour-texture reconstructions. Here, we report on R 2OBBIE-3D, an integrated system that combines a robotic arm, a high-resolution digital colour camera, an illumination basket of high-intensity light-emitting diodes and state-of-the-art 3D-reconstruction approaches. We demonstrate that R 2OBBIE generates accurate 3D models of biological objects between 1 and 100 cm, makes multiview photometric stereo scanning possible in practical processing times, and enables the capture of colour-texture and geometric resolutions better than 15 μm without the use of magnifying lenses. R 2OBBIE has the potential to greatly improve quantitative analyses of phenotypes in addition to providing multiple new applications in, e. g., biomedical science.

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          Accurate, dense, and robust multiview stereopsis.

          This paper proposes a novel algorithm for multiview stereopsis that outputs a dense set of small rectangular patches covering the surfaces visible in the images. Stereopsis is implemented as a match, expand, and filter procedure, starting from a sparse set of matched keypoints, and repeatedly expanding these before using visibility constraints to filter away false matches. The keys to the performance of the proposed algorithm are effective techniques for enforcing local photometric consistency and global visibility constraints. Simple but effective methods are also proposed to turn the resulting patch model into a mesh which can be further refined by an algorithm that enforces both photometric consistency and regularization constraints. The proposed approach automatically detects and discards outliers and obstacles and does not require any initialization in the form of a visual hull, a bounding box, or valid depth ranges. We have tested our algorithm on various data sets including objects with fine surface details, deep concavities, and thin structures, outdoor scenes observed from a restricted set of viewpoints, and "crowded" scenes where moving obstacles appear in front of a static structure of interest. A quantitative evaluation on the Middlebury benchmark shows that the proposed method outperforms all others submitted so far for four out of the six data sets.
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            Breaking the diffraction barrier: super-resolution imaging of cells.

            Anyone who has used a light microscope has wished that its resolution could be a little better. Now, after centuries of gradual improvements, fluorescence microscopy has made a quantum leap in its resolving power due, in large part, to advancements over the past several years in a new area of research called super-resolution fluorescence microscopy. In this Primer, we explain the principles of various super-resolution approaches, such as STED, (S)SIM, and STORM/(F)PALM. Then, we describe recent applications of super-resolution microscopy in cells, which demonstrate how these approaches are beginning to provide new insights into cell biology, microbiology, and neurobiology. Copyright © 2010 Elsevier Inc. All rights reserved.
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              Dynamics of Dpp signaling and proliferation control.

              Morphogens, such as Decapentaplegic (Dpp) in the fly imaginal discs, form graded concentration profiles that control patterning and growth of developing organs. In the imaginal discs, proliferative growth is homogeneous in space, posing the conundrum of how morphogen concentration gradients could control position-independent growth. To understand the mechanism of proliferation control by the Dpp gradient, we quantified Dpp concentration and signaling levels during wing disc growth. Both Dpp concentration and signaling gradients scale with tissue size during development. On average, cells divide when Dpp signaling levels have increased by 50%. Our observations are consistent with a growth control mechanism based on temporal changes of cellular morphogen signaling levels. For a scaling gradient, this mechanism generates position-independent growth rates.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                3 June 2015
                2015
                : 10
                : 6
                : e0126740
                Affiliations
                [1 ]Laboratory of Artificial & Natural Evolution (LANE), Department of Genetics & Evolution, University of Geneva, Geneva, Switzerland
                [2 ]SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
                University of Basel, SWITZERLAND
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: MCM AM. Performed the experiments: MCM AM MB LM. Analyzed the data: MCM AM MB LM. Contributed reagents/materials/analysis tools: MCM AM LM. Wrote the paper: MCM AM.

                Article
                PONE-D-14-42512
                10.1371/journal.pone.0126740
                4454658
                26039509
                0f14504e-c7b8-4915-8be2-b310ebd3c699
                Copyright @ 2015

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                : 23 September 2014
                : 7 April 2015
                Page count
                Figures: 6, Tables: 0, Pages: 18
                Funding
                This work was supported by the CADMOS program at the University of Geneva ( http://www.unige.ch; Switzerland), the Swiss National Science Foundation (FNSNF, http://www.snf.ch/en; grants 31003A_125060 and Sinergia CRSII3_132430), and the SystemsX.ch initiative (project EpiPhysX; http://www.systemsx.ch/projects/research-technology-and-development-projects/epiphysx).
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