Extraction of vocal tract area function from three‐dimensional magnetic resonance images using digital waveguide mesh

2008 ◽  
Vol 123 (5) ◽  
pp. 3736-3736
Author(s):  
Kenji Inoue ◽  
Hironori Takemoto ◽  
Tatsuya Kitamura ◽  
Shinobu Masaki ◽  
Hirotake Nakashima
Keyword(s):  
Magnetic Resonance ◽  
Vocal Tract ◽  
Three Dimensional ◽  
Magnetic Resonance Images ◽  
Area Function ◽  
Digital Waveguide Mesh ◽  
Digital Waveguide

Three-dimensional Vocal Tract Morphology Based on Multiple Magnetic Resonance Images Is Highly Reproducible During Sustained Phonation

2017 ◽  
Vol 31 (4) ◽  
pp. 504.e11-504.e20 ◽  
Author(s):  
Alexander Mainka ◽  
Ivan Platzek ◽  
Willy Mattheus ◽  
Mario Fleischer ◽  
Ann-Sophie Müller ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Vocal Tract ◽  
Three Dimensional ◽  
Magnetic Resonance Images

Vocal Tract Area Function for Vowels Using Three-Dimensional Magnetic Resonance Imaging. A Preliminary Study

2007 ◽  
Vol 21 (5) ◽  
pp. 522-530 ◽  
Author(s):  
Philippe Clément ◽  
Stéphane Hans ◽  
Dana M. Hartl ◽  
Shinji Maeda ◽  
Jacqueline Vaissière ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Vocal Tract ◽  
Three Dimensional ◽  
Resonance Imaging ◽  
Area Function ◽  
Preliminary Study

The Safety of Operating on Breasts With a History of Prior Reduction Mammoplasty: Dynamic Magnetic Resonance Imaging Analysis of Angiogenesis

2021 ◽  
Author(s):  
Joseph Kyu-hyung Park ◽  
Seokwon Park ◽  
Chan Yeong Heo ◽  
Jae Hoon Jeong ◽  
Bola Yun ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Three Dimensional ◽  
Venous Drainage ◽  
Reduction Mammoplasty ◽  
Magnetic Resonance Images ◽  
Areolar Complex ◽  
Internal Mammary ◽  
Initial Procedure ◽  
Nipple Sparing Mastectomy ◽  
Nipple Sparing

Abstract Background Vascularity of the nipple-areolar complex (NAC) is altered after reduction mammoplasty, which increases complications risks after repeat reduction or nipple-sparing mastectomy. Objectives To evaluate angiogenesis of the NAC via serial analysis of breast magnetic resonance images (MRIs). Methods Breast MRIs after reduction mammoplasty were analyzed for 35 patients (39 breasts) using three-dimensional reconstructions of maximal intensity projection images. All veins terminating at the NAC were classified as internal mammary, anterior intercostal, or lateral thoracic in origin. The vein with the largest diameter was considered the dominant vein. Images were classified based on the time since reduction: <6 months, 6-12 months, 12-24 months, >2 years. Results The average number of veins increased over time: 1.17 (<6 months), 1.56 (6–12 months), 1.64 (12–24 months), 1.73 (>2 years). Within 6 months, the pedicle was the only vein. Veins from other sources began to appear at 6–12 months. In most patients, at least two veins were available after 1 year. After 1 year, the internal mammary vein was the most common dominant vein regardless of the pedicle used. Conclusions In the initial 6 months after reduction mammoplasty, the pedicle is the only source of venous drainage; however, additional sources are available after 1 year. The internal thoracic vein was the dominant in most patients. Thus, repeat reduction mammoplasty or nipple-sparing mastectomy should be performed ≥1 year following the initial procedure. After 1 year, the superior or superomedial pedicle may represent the safest option when the previous pedicle is unknown.

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.

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