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dc.contributor.authorChang, Tsung-Yao
dc.contributor.authorPardo-Martin, Carlos
dc.contributor.authorAllalou, Amin Mohamed
dc.contributor.authorYanik, Mehmet Fatih
dc.contributor.authorWahlby, Carolina
dc.date.accessioned2014-10-21T18:22:03Z
dc.date.available2014-10-21T18:22:03Z
dc.date.issued2011-12
dc.date.submitted2011-09
dc.identifier.issn1473-0197
dc.identifier.issn1473-0189
dc.identifier.urihttp://hdl.handle.net/1721.1/91136
dc.description.abstractThe zebrafish larva is an optically-transparent vertebrate model with complex organs that is widely used to study genetics, developmental biology, and to model various human diseases. In this article, we present a set of novel technologies that significantly increase the throughput and capabilities of our previously described vertebrate automated screening technology (VAST). We developed a robust multi-thread system that can simultaneously process multiple animals. System throughput is limited only by the image acquisition speed rather than by the fluidic or mechanical processes. We developed image recognition algorithms that fully automate manipulation of animals, including orienting and positioning regions of interest within the microscope's field of view. We also identified the optimal capillary materials for high-resolution, distortion-free, low-background imaging of zebrafish larvae.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Director's New Innovator Award DP2 OD002989)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Transformative Research Award R01 NS073127)en_US
dc.description.sponsorshipDavid & Lucile Packard Foundation (Award in Science and Engineering)en_US
dc.description.sponsorshipBroad Institute of MIT and Harvard (SPARC Award)en_US
dc.description.sponsorshipFoxconn International Holdings Ltd.en_US
dc.description.sponsorshipAthinoula A. Martinos Center for Biomedical Imaging (Training Grant)en_US
dc.language.isoen_US
dc.publisherRoyal Society of Chemistryen_US
dc.relation.isversionofhttp://dx.doi.org/10.1039/c1lc20849gen_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcePMCen_US
dc.titleFully automated cellular-resolution vertebrate screening platform with parallel animal processingen_US
dc.typeArticleen_US
dc.identifier.citationChang, Tsung-Yao, Carlos Pardo-Martin, Amin Allalou, Carolina Wählby, and Mehmet Fatih Yanik. “Fully Automated Cellular-Resolution Vertebrate Screening Platform with Parallel Animal Processing.” Lab Chip 12, no. 4 (2012): 711.en_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technologyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorChang, Tsung-Yaoen_US
dc.contributor.mitauthorPardo-Martin, Carlosen_US
dc.contributor.mitauthorYanik, Mehmet Fatihen_US
dc.relation.journalLab on a Chipen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsChang, Tsung-Yao; Pardo-Martin, Carlos; Allalou, Amin; Wählby, Carolina; Yanik, Mehmet Fatihen_US
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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