Performance enhancement of deep learning based solutions for pharyngeal airway space segmentation on MRI scans

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: 1 Online-Ressource.

Language: Englisch

Bibliographic citation: Performance enhancement of deep learning based solutions for pharyngeal airway space segmentation on MRI scans ; volume:14 ; number:1 ; day:24 ; month:8 ; year:2024 ; pages:1-17 ; date:12.2024
Scientific reports ; 14, Heft 1 (24.8.2024), 1-17, 12.2024

Creator: Leeraha, Chattapatr
Kusakunniran, Worapan
Yodrabum, Nutcha
Chaisrisawadisuk, Sarut
Vathanophas, Vannipa
Siriapisith, Thanongchai

Contributor: SpringerLink (Online service)

DOI: 10.1038/s41598-024-70826-4

URN: urn:nbn:de:101:1-2411121019086.170915823587

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:33 AM CEST

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Leeraha, Chattapatr
Kusakunniran, Worapan
Yodrabum, Nutcha
Chaisrisawadisuk, Sarut
Vathanophas, Vannipa
Siriapisith, Thanongchai
SpringerLink (Online service)

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Performance enhancement of deep learning based solutions for pharyngeal airway space segmentation on MRI scans

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Other Objects (12)

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Diminution of pharyngeal segmentation and the evolution of the amniotes

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Early-onset pharyngeal airway collapse in infants: a retrospective single-center study

Accelerating segmentation of fossil CT scans through Deep Learning

Range image segmentation for tree detection in forest scans

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Diminution of pharyngeal segmentation and the evolution of the amniotes

Cephalometric Comparison of Pharyngeal Airway in Snoring and Non-Snoring Patients

Early-onset pharyngeal airway collapse in infants: a retrospective single-center study

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