Fully automatic segmentation of glottis and vocal folds in endoscopic laryngeal high-speed videos using a deep Convolutional LSTM Network

The objective investigation of the dynamic properties of vocal fold vibrations demands the recording and further quantitative analysis of laryngeal high-speed video (HSV). Quantification of the vocal fold vibration patterns requires as a first step the segmentation of the glottal area within each video frame from which the vibrating edges of the vocal folds are usually derived. Consequently, the outcome of any further vibration analysis depends on the quality of this initial segmentation process. In this work we propose for the first time a procedure to fully automatically segment not only the time-varying glottal area but also the vocal fold tissue directly from laryngeal high-speed video (HSV) using a deep Convolutional Neural Network (CNN) approach. Eighteen different Convolutional Neural Network (CNN) network configurations were trained and evaluated on totally 13,000 high-speed video (HSV) frames obtained from 56 healthy and 74 pathologic subjects. The segmentation quality of the best performing Convolutional Neural Network (CNN) model, which uses Long Short-Term Memory (LSTM) cells to take also the temporal context into account, was intensely investigated on 15 test video sequences comprising 100 consecutive images each. As performance measures the Dice Coefficient (DC) as well as the precisions of four anatomical landmark positions were used. Over all test data a mean Dice Coefficient (DC) of 0.85 was obtained for the glottis and 0.91 and 0.90 for the right and left vocal fold (VF) respectively. The grand average precision of the identified landmarks amounts 2.2 pixels and is in the same range as comparable manual expert segmentations which can be regarded as Gold Standard. The method proposed here requires no user interaction and overcomes the limitations of current semiautomatic or computational expensive approaches. Thus, it allows also for the analysis of long high-speed video (HSV)-sequences and holds the promise to facilitate the objective analysis of vocal fold vibrations in clinical routine. The here used dataset including the ground truth will be provided freely for all scientific groups to allow a quantitative benchmarking of segmentation approaches in future

Reliability of Subjective Endoscopic Parameters in the Differentiation of Essential Voice Tremor and Adductor Spasmodic Dysphonia Using High-Speed Videoendoscopy

Certain neurogenic voice disorders present with similar or overlapping audio perceptual voice characteristics. Developing reliable and standardized perceptual measures of vocal fold vibratory characteristics for such voice disorders can enable accurate diagnosis and lead to faster, targeted treatment. In this study, subjective perceptual vocal fold vibratory characteristics and the presence and absence of supraglottic events during phonation were investigated to differentiate between Adductor Spasmodic Dysphonia (ADSD) and Essential Vocal Fold Tremor (EVT) using high-speed videoendoscopy (HSV). The specific aims of the study were to 1) assess which subjective endoscopic vocal fold vibratory measures differentiate EVT from AdSD; and 2) assess the inter-rater and intra-rater reliability of the ratings. High speed video recordings of vibratory vocal fold motion were selected to conduct a retrospective analysis on existing data. The participants were classified into three groups: 16 participants with a diagnosis of Adductor Spasmodic Dysphonia, 8 participants with a clinical diagnosis of Essential Vocal Tremor, and 10 participants with a diagnosis of Both (AdSD with Tremor). The inclusion criteria for HSV data was the presence of a full view of true vocal folds and supraglottic structures during vibration. It was hypothesized that HSV vocal fold vibratory measures and supraglottic events would distinguish EVT and ADSD and these measures would be reliable. In addition, the vocal fold vibratory features would be more reliable than supraglottic events in differentiating between the groups. Results demonstrated mixed reliability for supraglottic and vocal fold vibratory parameters. None of the hypothesized supraglottic parameters demonstrated any significant distinction between diagnostic groups given the three raters’ responses. While all four vocal fold vibratory parameters revealed distinctive patterns between the three diagnostic categories, only two, right/left TVF symmetry and anterior/posterior TVF symmetry, met the requirements for both reliability and differentiation. For these parameters, EVT demonstrated greater vocal fold symmetry in comparison to AdSD; however, those with a differential diagnosis of both demonstrated the highest vocal fold symmetry

Models and Analysis of Vocal Emissions for Biomedical Applications

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies

Advances in Vibration Analysis Research

Vibrations are extremely important in all areas of human activities, for all sciences, technologies and industrial applications. Sometimes these Vibrations are useful but other times they are undesirable. In any case, understanding and analysis of vibrations are crucial. This book reports on the state of the art research and development findings on this very broad matter through 22 original and innovative research studies exhibiting various investigation directions. The present book is a result of contributions of experts from international scientific community working in different aspects of vibration analysis. The text is addressed not only to researchers, but also to professional engineers, students and other experts in a variety of disciplines, both academic and industrial seeking to gain a better understanding of what has been done in the field recently, and what kind of open problems are in this area