Evidence map›Paper›PMID 40157854›Full record

ArticleJournal of voice : official journal of the Voice Foundation2025

Uncertainty of Spatial Segmentation of High-Speed Videoendoscopy and Its Temporal and Spatial Dependency.

Hamzeh Ghasemzadeh, Maria E Powell, David S Ford, Dimitar D Deliyski

Abstract read
In one paragraph

Article in Journal of voice : official journal of the Voice Foundation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Hamzeh GhasemzadehCenter for Laryngeal Surgery and Voice Rehabilitation, Massachusetts General Hospital, Boston, MA; Department of Surgery, Harvard Medical School, Boston, MA; Department of Communicative Sciences and Disorders, Michigan State University, East Lansing, MI. Electronic address: hghasemzadeh@mgh.harvard.edu.
Maria E PowellDepartment of Otolaryngology-Head and Neck Surgery, Vanderbilt University Medical Center, Nashville, TN.
David S FordDepartment of Speech-Language Pathology, John G. Rangos, Sr. School of Health Sciences, Duquesne University, Pittsburgh, PA.
Dimitar D DeliyskiDepartment of Communicative Sciences and Disorders, Michigan State University, East Lansing, MI.

Funding

Towards Precision Assessment of Dysphonic Speech: From Vocal Fold Physiology to PerceptionR01DC019402 · NIDCD · MICHIGAN STATE UNIVERSITY · PI DIMITAR D DELIYSKI · 2022 to 2026
$3.1M
Cognitive and Biological Mechanisms in Pediatric Voice TherapyR01DC017923 · NIDCD · UNIVERSITY OF DELAWARE · PI VERDOLINI, KATHERINE · 2019 to 2023
$3.1M
Objective assessment of vocal fatigue in laboratory and real-world settingsK99DC021235 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI GHASEMZADEH, HAMZEH · 2023 to 2024
$266k
NIDCD NIH HHS K99 DC021235NIDCD NIH HHS R01 DC017923NIDCD NIH HHS R01 DC019402
6 · The paper itself

Abstract

objectiveSpatial segmentation of high-speed videoendoscopy (HSV) is the process that detects the edges of the vocal folds and represents them in analytic form. The level of spatial segmentation uncertainty (ie, how close vs. far apart different experts marked the edges of the vocal folds) can have a great impact on the level of uncertainty of the final measures (ie, their dispersion). This study quantified the uncertainty of spatial segmentation and investigated its dependency on the phase of the glottal cycle and the location of vocal fold edges along the anterior-posterior direction.

methodThree experts manually segmented the vocal fold edges of twelve HSV recordings using an iterative process consisting of an initial segmentation followed by a blinded reconciliation phase. Segmentation uncertainty was computed as the distance in pixels between the three-segmented edges at the end of the iterative process. The relationships between segmentation uncertainty and different sections of the glottis along the anterior-posterior direction and the relationships between segmentation uncertainty and different phases of the glottal cycle were quantified.

resultsSegmentation uncertainties of the anterior and the posterior sections of the glottis were significantly higher than the middle section, while uncertainty of the anterior section was the highest and 40% larger than the middle section. The average segmentation uncertainty and normalized glottal area were positively correlated. Segmentation uncertainty of the most open glottal configurations was 31% larger than the most closed glottal configuration.

conclusionThe uncertainty of spatial segmentation of the vocal fold edges depends on the phase of the glottal cycle and the location of the edge along the anterior-posterior direction; hence, it is expected for different HSV measures to have different levels of uncertainties. The implications of these findings for vocal fold velocity measures are discussed. Additionally, the findings from this study could provide direction for future automated spatial segmentation methods and for creating a robust and reliable automated HSV processing pipeline.

Indexed as

Uncertainty—Reliability—Spatial segmentation—Vocal fold edges—Vocal fold velocity.

Identifiers

PMID40157854
PMCPMC12353461

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