Exploring Techniques to Analyze Chest X-Ray Using Gaze Data

dc.contributor.advisorNguyen, Hien Van
dc.contributor.committeeMemberHan, Zhu
dc.contributor.committeeMemberBenhaddou, Driss
dc.creatorKonda, Akhilkumar Kumar
dc.date.accessioned2018-11-30T17:48:58Z
dc.date.available2018-11-30T17:48:58Z
dc.date.createdMay 2018
dc.date.issued2018-05
dc.date.submittedMay 2018
dc.date.updated2018-11-30T17:48:59Z
dc.description.abstractEven with the current technological advancements in the field of radiology, the error rate in radiology diagnosis has not decreased significantly. These errors result in thousands of deaths in the US alone. There is a need for change in radiological practices as the current system still relies on small group didactic lectures and informal tutorials. There is no systematic and quantitative way to measure the performance of a radiologist over time. This thesis addresses this issue by proposing the framework of a new toolkit that can provide thoracic radiology education with quantitative measurement and an evaluation of radiologist's ability to detect thoracic imaging abnormalities. It also provides a rich analysis of gaze patterns for learners to gain insight and self-reflect on their mistakes by using clustering, warping and classifier techniques.
dc.description.departmentElectrical and Computer Engineering, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10657/3486
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectRadiologist
dc.subjectGaze Data
dc.subjectMachine learning
dc.titleExploring Techniques to Analyze Chest X-Ray Using Gaze Data
dc.type.dcmiText
dc.type.genreThesis
local.embargo.lift2020-05-01
local.embargo.terms2020-05-01
thesis.degree.collegeCullen College of Engineering
thesis.degree.departmentElectrical and Computer Engineering, Department of
thesis.degree.disciplineComputer and Systems Engineering
thesis.degree.grantorUniversity of Houston
thesis.degree.levelMasters
thesis.degree.nameMaster of Science
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