Dataset Information

Three-dimensional reconstruction of human vocal folds and standard laryngeal cartilages using computed tomography scan data.

ABSTRACT: Three-dimensional (3D) computer models of the human larynx are useful tools for research and for eventual clinical applications. Recently, computed tomography (CT) scanning and magnetic resonance imaging (MRI) have been used to recreate realistic models of human larynx. In the present study, CT images were used to create computer models of vocal folds, vocal tract, and laryngeal cartilages, and the procedure to create solid models are explained in details. Vocal fold and vocal tract 3D models of healthy and postsurgery larynges during phonation and respiration were created and morphometric parameters were quantified. The laryngeal framework of eight patients was also reconstructed from CT scan images. For each cartilage, morphometric landmarks were measured on the basis of their importance for biomechanical modeling. A quantitative comparison was made between measured values from the reconstructions and those from human excised larynges in literature. The good agreement between these measurements supports the accuracy of CT scan-based 3D models. Generic standard models of the laryngeal framework were created using known features in modeling softwares. They were created based on the morphometric landmark dimensions previously defined, preserving all biomechanically important dimensions. These models are accessible, subject independent, easy to use for computational simulations, and make the comparisons between different studies possible.

SUBMITTER: Bakhshaee H

PROVIDER: S-EPMC3834040 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

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Publications

Three-dimensional reconstruction of human vocal folds and standard laryngeal cartilages using computed tomography scan data.

Bakhshaee Hani H Moro Christina C Kost Karen K Mongeau Luc L

Journal of voice : official journal of the Voice Foundation 20131008 6

Three-dimensional (3D) computer models of the human larynx are useful tools for research and for eventual clinical applications. Recently, computed tomography (CT) scanning and magnetic resonance imaging (MRI) have been used to recreate realistic models of human larynx. In the present study, CT images were used to create computer models of vocal folds, vocal tract, and laryngeal cartilages, and the procedure to create solid models are explained in details. Vocal fold and vocal tract 3D models of ...[more]

PMID: 24119643

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Project description: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.

Dataset Information

Three-dimensional reconstruction of human vocal folds and standard laryngeal cartilages using computed tomography scan data.

Publications

Three-dimensional reconstruction of human vocal folds and standard laryngeal cartilages using computed tomography scan data.

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