Advancing life science with adaptive intelligent microscopy

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dc.contributor.advisorSt-Pierre, Francois
dc.contributor.advisorAazhang, Behnaam
dc.creatorSafaei, Seyed Mojtaba
dc.date.accessioned2022-09-23T21:44:30Z
dc.date.created2022-05
dc.date.issued2022-04-22
dc.date.submittedMay 2022
dc.date.updated2022-09-23T21:44:30Z
dc.descriptionEMBARGO NOTE: This item is embargoed until 2024-05-01
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.
dc.embargo.lift2024-05-01
dc.embargo.terms2024-05-01
dc.format.mimetypeapplication/pdf
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>.
dc.identifier.urihttps://hdl.handle.net/1911/113342
dc.language.isoeng
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.
dc.subjectCLM
dc.subjectclosed-loop
dc.subjectevent-driven
dc.subjectadaptive microscopy
dc.subjectsmart microscopy
dc.subjectintelligent microscopy
dc.titleAdvancing life science with adaptive intelligent microscopy
dc.typeThesis
dc.type.materialText
thesis.degree.departmentElectrical and Computer Engineering
thesis.degree.disciplineEngineering
thesis.degree.grantorRice University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science
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