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dc.contributor.advisorNir Shavit.en_US
dc.contributor.authorStoller, Jonathan (Jonathan M.)en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2017-01-12T18:18:20Z
dc.date.available2017-01-12T18:18:20Z
dc.date.copyright2016en_US
dc.date.issued2016en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/106377
dc.descriptionThesis: M. Eng. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (page 47).en_US
dc.description.abstractIn this thesis, I designed an algorithm that traces neurons through the images of various datasets extracted from mouse brains. The algorithm is implemented in Python and relies on the output of a recently developed Fully Convolutional Neural Network (implemented in C) that runs on the underlying images. The images themselves are generated using state of the art technologies that provide high resolution and extremely accurate representations of the original brain matter. The algorithm is part of the combined efforts of MIT's Computational Connectomics Group.en_US
dc.description.statementofresponsibilityby Jonathan Stoller.en_US
dc.format.extent47 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleOnline neuron reconstructionen_US
dc.typeThesisen_US
dc.description.degreeM. Eng. in Computer Science and Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc967348545en_US


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