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Larynx

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A Deep Learning Enhanced Novel Software Tool for Laryngeal Dynamics Analysis.

Journal of speech, language, and hearing research : JSLHR
Purpose High-speed videoendoscopy (HSV) is an emerging, but barely used, endoscopy technique in the clinic to assess and diagnose voice disorders because of the lack of dedicated software to analyze the data. HSV allows to quantify the vocal fold osc...

Measurement of laryngeal elevation by automated segmentation using Mask R-CNN.

Medicine
The methods of measuring laryngeal elevation during swallowing are time-consuming. We aimed to propose a quick-to-use neural network (NN) model for measuring laryngeal elevation quantitatively using anatomical structures auto-segmented by Mask region...

A Deep Learning Approach for Quantifying Vocal Fold Dynamics During Connected Speech Using Laryngeal High-Speed Videoendoscopy.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: Voice disorders are best assessed by examining vocal fold dynamics in connected speech. This can be achieved using flexible laryngeal high-speed videoendoscopy (HSV), which enables us to study vocal fold mechanics with high temporal details....

Endoluminal larynx anatomy model - towards facilitating deep learning and defining standards for medical images evaluation with artificial intelligence algorithms.

Otolaryngologia polska = The Polish otolaryngology
The pioneering nature of this work covers the answers to two questions: (1) Is an up-to-date anatomical model of the larynx needed for modern endoscopic diagnostics, and (2) can such a digital segmentation model be utilized for deep learning purposes...

An Improvised Deep-Learning-Based Mask R-CNN Model for Laryngeal Cancer Detection Using CT Images.

Sensors (Basel, Switzerland)
Recently, laryngeal cancer cases have increased drastically across the globe. Accurate treatment for laryngeal cancer is intricate, especially in the later stages. This type of cancer is an intricate malignancy inside the head and neck area of patien...

Predictive Outcomes of Deep Learning Measurement of the Anterior Glottic Angle in Bilateral Vocal Fold Immobility.

The Laryngoscope
OBJECTIVE: (1) To compare maximum glottic opening angle (anterior glottic angle, AGA) in patients with bilateral vocal fold immobility (BVFI), unilateral vocal fold immobility (UVFI) and normal larynges (NL), and (2) to correlate maximum AGA with pat...

Localization and quantification of glottal gaps on deep learning segmentation of vocal folds.

Scientific reports
The entire glottis has mostly been the focus in the tracking of the vocal folds, both manually and automatically. From a treatment point of view, the various regions of the glottis are of specific interest. The aim of the study was to test if it was ...

A multi-stage transfer learning strategy for diagnosing a class of rare laryngeal movement disorders.

Computers in biology and medicine
BACKGROUND: It remains hard to directly apply deep learning-based methods to assist diagnosing essential tremor of voice (ETV) and abductor and adductor spasmodic dysphonia (ABSD and ADSD). One of the main challenges is that, as a class of rare laryn...

Deep learning in endoscopy: the importance of standardisation.

Acta otorhinolaryngologica Italica : organo ufficiale della Societa italiana di otorinolaringologia e chirurgia cervico-facciale

[Diagnosis of benign laryngeal tumors using neural network].

Vestnik otorinolaringologii
The article describes our experience in developing and training an artificial neural network based on artificial intelligence algorithms for recognizing the characteristic features of benign laryngeal tumors and variants of the norm of the larynx bas...