Multi-Purpose Chest X-Ray Analytics System Using Deep Learning Techniques

Simple item page
dc.contributor.advisorNguyen, Hien Van
dc.contributor.committeeMemberMayerich, David
dc.contributor.committeeMemberShah, Shishir Kirit
dc.creatorShah, Tanay Jignesh
dc.date.accessioned2018-11-30T16:24:34Z
dc.date.available2018-11-30T16:24:34Z
dc.date.createdMay 2018
dc.date.issued2018-05
dc.date.submittedMay 2018
dc.date.updated2018-11-30T16:24:34Z
dc.description.abstractThere has been rapid and tremendous progress in the past few years in the field of deep learning, mainly due to the availability of computational power and the vast amount of data. Deep neural networks have resulted in state-of-the-art performances in classification, detection, and segmentation in comparison to previous shallow methodologies built upon hand-crafted image features. This progress has yielded a rise in performance of medical imaging analysis as well. Chest X-ray imaging is one of the most accessible medical imaging technique for diagnosis of multiple diseases. With the availability of ChestX-ray14, which is a massive dataset of chest X-ray images, we can use deep learning techniques for various tasks like classification, detection, segmentation, etc. This thesis explores deep learning techniques such as convolutional neural networks and generative adversarial networks for applications of content-based image retrieval, image generation for different pathologies, and recognition of pathologies in chest X-rays.
dc.description.departmentElectrical and Computer Engineering, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10657/3459
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.subjectChest X-rays
dc.subjectDeep learning
dc.titleMulti-Purpose Chest X-Ray Analytics System Using Deep Learning Techniques
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.disciplineElectrical Engineering
thesis.degree.grantorUniversity of Houston
thesis.degree.levelMasters
thesis.degree.nameMaster of Science

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
SHAH-THESIS-2018.pdf
Size:
7.33 MB
Format:
Adobe Portable Document Format
Download

License bundle

Now showing 1 - 2 of 2
No Thumbnail Available
Name:
PROQUEST_LICENSE.txt
Size:
4.43 KB
Format:
Plain Text
Description:
Download
No Thumbnail Available
Name:
LICENSE.txt
Size:
1.82 KB
Format:
Plain Text
Description:
Download

Collections

Published ETD Collection