Advancing life science with adaptive intelligent microscopy

dc.contributor.advisorSt-Pierre, Francoisen_US
dc.contributor.advisorAazhang, Behnaamen_US
dc.creatorSafaei, Seyed Mojtabaen_US
dc.date.accessioned2022-09-23T21:44:30Zen_US
dc.date.created2022-05en_US
dc.date.issued2022-04-22en_US
dc.date.submittedMay 2022en_US
dc.date.updated2022-09-23T21:44:30Zen_US
dc.description.abstractBiology is dynamic: the location, shape, and function of molecules and cells change with time. When studying biological systems, it is critical to adapt data collection and analysis to fit their current states. However, the lack of real-time interactions in traditional microscopy makes it impossible to guide the experiments and adapt to the biological events. In this thesis, we introduce closed-loop microscopy (CLM) approaches that address the current shortcomings by providing real-time interactions between acquisition and analysis. CLM is implemented in an event-driven way; acquisition events notify the downstream analysis, resulting in feedback that triggers real-time actions. CLM is particularly suited for long experiments that study rare biological events; experiments in which adapting to the real-time changes increases the probability of success. We demonstrated examples in which CLM reduced sample size variation across trials, achieved five times higher throughput in fluorescent protein characterization, and enabled the study of rotavirus at low multiplicities of infection.en_US
dc.embargo.lift2024-05-01en_US
dc.embargo.terms2024-05-01en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationSafaei, Seyed Mojtaba. "Advancing life science with adaptive intelligent microscopy." (2022) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/113342">https://hdl.handle.net/1911/113342</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/113342en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectCLMen_US
dc.subjectclosed-loopen_US
dc.subjectevent-drivenen_US
dc.subjectadaptive microscopyen_US
dc.subjectsmart microscopyen_US
dc.subjectintelligent microscopyen_US
dc.titleAdvancing life science with adaptive intelligent microscopyen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentElectrical and Computer Engineeringen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
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