Automatic Multiple Articulator Segmentation in Dynamic Speech MRI Using a Protocol Adaptive Stacked Transfer Learning U-NET Model

Automatic Multiple Articulator Segmentation in Dynamic Speech MRI Using a Protocol Adaptive Stacked Transfer Learning U-NET Model

Dynamic magnetic resonance imaging has emerged as a powerful modality for investigating upper-airway function during speech production. Analyzing the changes in the vocal tract airspace, including the position of soft-tissue articulators (e.g., the tongue and velum), enhances our understanding of sp...

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Bibliographic Details
Main Authors: Subin Erattakulangara, Karthika Kelat, David Meyer, Sarv Priya, Sajan Goud Lingala
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Bioengineering
Subjects:
dynamic speech MRI
articulator segmentation
protocol adaptiveness
transfer learning
Online Access:https://www.mdpi.com/2306-5354/10/5/623

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https://www.mdpi.com/2306-5354/10/5/623

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