Publication:
Vocal tract airway tissue boundary tracking for rtMRI using shape and appearance priors

dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.departmentGraduate School of Sciences and Engineering
dc.contributor.kuauthorAsadiabadi, Sasan
dc.contributor.kuauthorErzin, Engin
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.date.accessioned2024-11-09T23:02:26Z
dc.date.issued2017
dc.description.abstractKnowledge about the dynamic shape of the vocal tract is the basis of many speech production applications such as, articulatory analysis, modeling and synthesis. Vocal tract airway tissue boundary segmentation in the mid-sagittal plane is necessary as an initial step for extraction of the cross-sectional area function. This segmentation problem is however challenging due to poor resolution of real-time speech MRI, grainy noise and the rapidly varying vocal tract shape. We present a novel approach to vocal tract airway tissue boundary tracking by training a statistical shape and appearance model for human vocal tract. We manually segment a set of vocal tract profiles and utilize a statistical approach to train a shape and appearance model for the tract. An active contour approach is employed to segment the airway tissue boundaries of the vocal tract while restricting the curve movement to the trained shape and appearance model. Then the contours in subsequent frames are tracked using dense motion estimation methods. Experimental evaluations over the mean square error metric indicate significant improvements compared to the state-of-the-art.
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.openaccessNO
dc.description.sponsoredbyTubitakEuN/A
dc.identifier.doi10.21437/Interspeech.2017-1016
dc.identifier.isbn978-1-5108-4876-4
dc.identifier.issn2308-457X
dc.identifier.scopus2-s2.0-85039162966
dc.identifier.urihttps://doi.org/10.21437/Interspeech.2017-1016
dc.identifier.urihttps://hdl.handle.net/20.500.14288/8277
dc.identifier.wos457505000129
dc.keywordsSpeech production
dc.keywordsVocal tract
dc.keywordsContour tracking
dc.language.isoeng
dc.publisherIsca-Int Speech Communication Assoc
dc.relation.ispartof18th Annual Conference of The International Speech Communication Association (Interspeech 2017), Vols 1-6: Situated Interaction
dc.subjectComputer science
dc.subjectArtificial intelligence
dc.subjectEngineering
dc.subjectElectrical and electronic
dc.titleVocal tract airway tissue boundary tracking for rtMRI using shape and appearance priors
dc.typeConference Proceeding
dspace.entity.typePublication
local.contributor.kuauthorAsadiabadi, Sasan
local.contributor.kuauthorErzin, Engin
local.publication.orgunit1GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
local.publication.orgunit1College of Engineering
local.publication.orgunit2Department of Computer Engineering
local.publication.orgunit2Graduate School of Sciences and Engineering
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