@article {49466, title = {In toto imaging and reconstruction of post-implantation mouse development at the single-cell level.}, journal = {Cell}, volume = {175}, year = {2018}, month = {2018 Oct 10}, pages = {859-876}, abstract = {

The mouse embryo has long been central to the study of mammalian development; however, elucidating the cell behaviors governing gastrulation and the formation of tissues and organs remains a fundamental challenge. A major obstacle is the lack of live imaging and image analysis technologies capable of systematically following cellular dynamics across the developing embryo. We developed a light-sheet microscope that adapts itself to the dramatic changes in size, shape, and optical properties of the post-implantation\ mouse embryo and captures its development from gastrulation to early organogenesis at\ the cellular level. We furthermore developed a computational framework for reconstructing long-term cell tracks, cell divisions, dynamic fate maps, and maps of tissue morphogenesis across the entire embryo. By jointly analyzing cellular dynamics in multiple embryos registered in space and time, we built a dynamic atlas of post-implantation mouse development that, together with our microscopy and computational methods, is provided as a resource.

}, issn = {1097-4172}, doi = {10.1016/j.cell.2018.09.031}, author = {McDole, Katie and Guignard, Leo and Amat, Fernando and Berger, Andrew and Malandain, Gr{\'e}goire and Royer, Lo{\"\i}c A and Turaga, Srinivas C and Branson, Kristin and Keller, Philipp J} } @article {49487, title = {A practical guide to adaptive light-sheet microscopy.}, journal = {Nature Protocols}, volume = {13}, year = {2018}, month = {2018 Oct 26}, pages = {2462{\textendash}2500}, abstract = {

We describe the implementation and use of an adaptive imaging framework for optimizing spatial resolution and signal strength in a light-sheet microscope. The framework, termed AutoPilot, comprises hardware and software modules for automatically measuring and compensating for mismatches between light-sheet and detection focal planes in living specimens. Our protocol enables researchers to introduce adaptive imaging capabilities in an existing light-sheet microscope or use our SiMView microscope blueprint to set up a new adaptive multiview light-sheet microscope. The protocol describes (i) the mechano-optical implementation of the adaptive imaging hardware, including technical drawings for all custom microscope components; (ii) the algorithms and software library for automated adaptive imaging, including the pseudocode and annotated source code for all software modules; and (iii) the execution of adaptive imaging experiments, as well as the configuration and practical use of the AutoPilot framework. Setup of the adaptive imaging hardware and software takes 1-2 weeks each. Previous experience with light-sheet microscopy and some familiarity with software engineering and building of optical instruments are recommended. Successful implementation of the protocol recovers near diffraction-limited performance in many parts of typical multicellular organisms studied with light-sheet microscopy, such as fruit fly and zebrafish embryos, for which resolution and signal strength are improved two- to fivefold.

}, issn = {1750-2799}, doi = {10.1038/s41596-018-0043-4}, author = {Royer, Lo{\"\i}c A and Lemon, William C and Chhetri, Raghav K and Keller, Philipp J} } @article {47987, title = {Adaptive light-sheet microscopy for long-term, high-resolution imaging in living organisms.}, journal = {Nature Biotechnology}, volume = {34}, year = {2016}, month = {2016 Oct 31}, pages = {1267-78}, abstract = {

Optimal image quality in light-sheet microscopy requires a perfect overlap between the illuminating light sheet and the focal plane of the detection objective. However, mismatches between the light-sheet and detection planes are common owing to the spatiotemporally varying optical properties of living specimens. Here we present the AutoPilot framework, an automated method for spatiotemporally adaptive imaging that integrates (i) a multi-view light-sheet microscope capable of digitally translating and rotating light-sheet and detection planes in three dimensions and (ii) a computational method that continuously optimizes spatial resolution across the specimen volume in real time. We demonstrate long-term adaptive imaging of entire developing zebrafish (Danio rerio) and Drosophila melanogaster embryos and perform adaptive whole-brain functional imaging in larval zebrafish. Our method improves spatial resolution and signal strength two to five-fold, recovers cellular and sub-cellular structures in many regions that are not resolved by non-adaptive imaging, adapts to spatiotemporal dynamics of genetically encoded fluorescent markers and robustly optimizes imaging performance during large-scale morphogenetic changes in living organisms.

}, issn = {1546-1696}, doi = {10.1038/nbt.3708}, author = {Royer, Lo{\"\i}c A and Lemon, William C and Chhetri, Raghav K and Wan, Yinan and Coleman, Michael and Myers, Eugene W and Keller, Philipp J} } @conference {48179, title = {Convexity shape constraints for image segmentation.}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2016}, month = {2016 Jun 27}, publisher = {IEEE}, organization = {IEEE}, address = {Las Vegas, NV}, abstract = {

Segmenting an image into multiple components is a central task in computer vision. In many practical scenarios, prior knowledge about plausible components is available. Incorporating such prior knowledge into models and algorithms for image segmentation is highly desirable, yet can be non-trivial. In this work, we introduce a new approach that allows, for the first time, to constrain some or all components of a segmentation to have convex shapes. Specifically, we extend the Minimum Cost Multicut Problem by a class of constraints that enforce convexity. To solve instances of this NP-hard integer linear program to optimality, we separate the proposed constraints in the branch-and-cut loop of a state-of-the-art ILP solver. Results on photographs and micrographs demonstrate the effectiveness of the approach as well as its advantages over the state-of-the-art heuristic.

}, doi = {10.1109/CVPR.2016.50}, author = {Royer, Lo{\"\i}c A and Richmond, David L and Rother, Carsten and Andres, Bjoern and Kainmueller, Dagmar} }