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Deep Learning Based Computer-aided Detection and Diagnosis Systems for Medical Imaging

dc.contributor.advisorKo, Seok-Bum
dc.contributor.committeeMemberLi, Xingyu
dc.contributor.committeeMemberWu, FangXiang
dc.contributor.committeeMemberChen, Li
dc.contributor.committeeMemberWahid, Khan
dc.contributor.committeeMemberMehr, Aryan
dc.creatorWang, Yi
dc.date.accessioned2023-04-03T18:09:44Z
dc.date.copyright2023
dc.date.created2023-03
dc.date.issued2023-04-03
dc.date.submittedMarch 2023
dc.date.updated2023-04-03T18:09:45Z
dc.description.abstract
This item is under an embargo. Access to the abstract will not be permitted until 2024-04-03
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/10388/14549
dc.language.isoen
dc.subjectComputer-aided Diagnosis System
dc.subjectComputer-aided Detection System
dc.subjectDeep Learning
dc.subjectConvolutional Neural Network
dc.subjectLung Nodule Classification
dc.subjectBreast Lesion Classification
dc.subjectMediastinal Lesion Segmentation
dc.titleDeep Learning Based Computer-aided Detection and Diagnosis Systems for Medical Imaging
dc.typeThesis
dc.type.materialtext
local.embargo.lift2024-04-03
local.embargo.terms2024-04-03
thesis.degree.departmentElectrical and Computer Engineering
thesis.degree.disciplineElectrical Engineering
thesis.degree.grantorUniversity of Saskatchewan
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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