Robust unsupervised extraction of vocal tract variables from midsagittal real-time magnetic resonance image sequences using region segmentation

2007 ◽  
Vol 122 (5) ◽  
pp. 3030
Author(s):  
Erik Bresch ◽  
Shrikanth Narayanan
Keyword(s):  
Magnetic Resonance ◽  
Real Time ◽  
Magnetic Resonance Image ◽  
Vocal Tract ◽  
Image Sequences ◽  
Region Segmentation

Direct estimation of articulatory kinematics from real-time magnetic resonance image sequences

2011 ◽  
Author(s):  
Michael Proctor ◽  
Adam Lammert ◽  
Athanasios Katsamanis ◽  
Louis Goldstein ◽  
Christina Hagedorn ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Real Time ◽  
Magnetic Resonance Image ◽  
Image Sequences ◽  
Direct Estimation

scholarly journals Semi-automatic method for analysing vocal tract morphology from real-time magnetic resonance images

2021 ◽  
Author(s):  
Michel Belyk ◽  
Christopher Carignan ◽  
Carolyn McGettigan
Keyword(s):  
Magnetic Resonance ◽  
Real Time ◽  
Vocal Tract ◽  
Structural Features ◽  
Magnetic Resonance Images ◽  
Training Data ◽  
Surrounding Tissue ◽  
User Input ◽  
Internal Structures ◽  
Automated Processing

Real-time magnetic resonance imaging is a technique that provides high contrast videographic data of the vocal tract that allow researchers to observe the internal structures that shape the sounds of speech. However, structural features need to be extracted from these vocal tract images to make them useful to researchers. We have developed a semi-automated processing pipeline that produces outlines of the vocal tract to quantify vocal tract morphology. Our approach uses simple tissue classification constrained to pixels that analysts have identified as likely to contain the vocal tract and surrounding tissue. This approach is supplemented with multiple opportunities for the analyst to intervene in order to ensure that outputs are robust to errors. Although this approach is more labour intensive than more fully automated alternatives, these costs are offset by the benefits of improving the quality of measurements. We demonstrate that this pipeline can be generalised to a range of datasets and that it remains reliable across analysts, particularly among analysts with vocal tract expertise. The pipeline’s reliance on user input presents a challenge to scalability if applied to very large. Measurements produced by this pipeline could be provide a broader scope of training data for fully automated methods in an effort to improve their generalisability.

Real-Time Ex-Vivo Magnetic Resonance Image—Guided Dissection of Human Brain White Matter: A Proof-of-Principle Study

2019 ◽  
Vol 125 ◽  
pp. 198-206 ◽  
Author(s):  
Giacomo Bertolini ◽  
Emanuele La Corte ◽  
Domenico Aquino ◽  
Elena Greco ◽  
Zefferino Rossini ◽  
...  
Keyword(s):  
White Matter ◽  
Magnetic Resonance ◽  
Human Brain ◽  
Real Time ◽  
Magnetic Resonance Image ◽  
Ex Vivo ◽  
Image Guided ◽  
Brain White Matter ◽  
Proof Of Principle
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