The Next 10 Years in Voice Evaluation and Treatment

Barkmeier-Kraemer, Julie; Patel, Rita R.

doi:10.1055/s-0036-1583547

Cited by 7 publications

(3 citation statements)

References 66 publications

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“…It is anticipated that the examination of laryngeal endoscopic images will allow early detection of pathologies [5]. Vocal folds, as the main functional organ within the larynx, are sensitive structures for surgery.…”

Section: Introductionmentioning

confidence: 99%

A dataset of laryngeal endoscopic images with comparative study on convolution neural network-based semantic segmentation

et al. 2019

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Purpose Automated segmentation of anatomical structures in medical image analysis is a prerequisite for autonomous diagnosis as well as various computer and robot aided interventions. Recent methods based on deep convolutional neural networks (CNN) have outperformed former heuristic methods. However, those methods were primarily evaluated on rigid, real-world environments. In this study, existing segmentation methods were evaluated for their use on a new dataset of transoral endoscopic exploration. Methods Four machine learning based methods SegNet, UNet, ENet and ErfNet were trained with supervision on a novel 7-class dataset of the human larynx. The dataset contains 536 manually segmented images from two patients during laser incisions. The Intersection-over-Union (IoU) evaluation metric was used to measure the accuracy of each method. Data augmentation and network ensembling were employed to increase segmentation accuracy. Stochastic inference was used to show uncertainties of the individual models. Patient-to-patient transfer was investigated using patient-specific fine-tuning. Results In this study, a weighted average ensemble network of UNet and ErfNet was best suited for the segmentation of laryngeal soft tissue with a mean IoU of 84.7 %. The highest efficiency was achieved by ENet with a mean inference time of 9.22 ms per image. It is shown that 10 additional images from a new patient are sufficient for patient-specific fine-tuning. Conclusion CNN-based methods for semantic segmentation are applicable to endoscopic images of laryngeal soft tissue. The segmentation can be used for active constraints or to monitor morphological changes and autonomously detect pathologies. Further improvements could be achieved by using a larger dataset or training the models in a self-supervised manner on additional unlabeled data.

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Section: Introductionmentioning

confidence: 99%

A dataset of laryngeal endoscopic images with comparative study on convolution neural network-based semantic segmentation

et al. 2019

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“…Udowodniono, że nawet krótkie szkolenia teoretyczne oraz ambulatoryjne kursy emisji głosu w połączeniu z fizjoterapią i psychoterapią wpływają na poprawę parametrów głosu. W warunkach codziennego, kilkugodzinnego obciążenia wysiłkiem leczenie zaburzeń głosu nie jest jednak łatwe [5,6].…”

Section: Wstępunclassified

The teachers’ voice rehabilitation in sanatorium conditions

Sinkiewicz¹,

Garstecka²,

Mackiewicz‐Nartowicz³

et al. 2021

Med Pr

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Wstęp: Schorzenia narządu głosu zajmują 3 miejsce wśród rozpoznawanych chorób zawodowych w Polsce. Nadal istnieje potrzeba wdrażania skutecznych i ekonomicznych metod prewencji pierwotnej i wtórnej zaburzeń głosu u nauczycieli. Celem pracy była ocena skuteczności kompleksowej rehabilitacji głosu u nauczycieli prowadzonej w warunkach szpitala uzdrowiskowego. Materiał i metody: Przedstawiono wyniki kompleksowej rehabilitacji głosu przeprowadzonej podczas 24-dniowego turnusu sanatoryjnego u 100 nauczycielek ze stażem pracy 10-30 lat (M = 17 lat). W pierwszym i ostatnim dniu turnusu wykonano badania laryngologiczne i foniatryczne [czas fonacji (maximum phonation time -MPT), ocenę percepcyjną głosu w skali GRBAS, badanie laryngowideostroboskopowe, analizę akustyczną głosu], wypełnienie Kwestionariusza samooceny głosu (Voice Handicap Index -VHI), ocenę logopedyczną i audiometrię tonalną. W zakres programu terapeutycznego wchodziły: zajęcia edukacyjne dotyczące higieny głosu, terapia głosu, fizjoterapia i psychoterapia. Efekty rehabilitacji sanatoryjnej pacjenci oceniali również w badaniu ankietowym. Wyniki: Stwierdzono poprawę obiektywnych parametrów akustycznych, oceny percepcyjnej głosu, samoceny głosu VHI i MPT. Zmiany w sposobie fonacji potwierdzono w badaniu laryngowideostroboskopowym, w którym obserwowane zwarcie fonacyjne poprawiło się znamiennie u 30% badanych. W ankiecie oceniającej korzyści z sanatoryjnej rehabilitacji głosu 97% uczestników potwierdziło skuteczność i celowość okresowego powtarzania takiej rehabilitacji. Wnioski: Wyniki przedstawionych badań i pozytywne oceny uczestników rehabilitacji sanatoryjnej potwierdzają skuteczność sanatoryjnej terapii zawodowych zaburzeń głosu. Leczenie i rehabilitacja w formie stacjonarnej powinny zmierzać do poprawy głosu oraz kontynuacji pracy zawodowej. Tak ukierunkowane postępowanie może przyczynić się do zmniejszenia nakładów finansowych związanych z leczeniem, urlopami dla poratowania zdrowia i rentami zawodowymi. Med. Pr. 2021;72(4)

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“…The effectiveness of complex voice rehabilitation programs in ambulatory care has been assessed by many authors [12][13][14][15]. It was observed that vocal hygiene training significantly improves voice quality and reduces disorder symptoms [16,17]. Multicenter efforts to improve quality of care for persons professionally and strenuously using their voice resulted in the development of an interdisciplinary 24-day vocal prophylactic and rehabilitation program conducted in health resort hospitals [18].…”

Section: Introductionmentioning

confidence: 99%

The Effectiveness of Rehabilitation of Occupational Voice Disorders in a Health Resort Hospital Environment

Sinkiewicz

Garstecka

Mackiewicz‐Nartowicz

et al. 2021

JCM

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Background: The aim of this study was to present a rehabilitation program of occupational voice disorders for teachers, conducted in the form of health resort stays, and evaluate its effectiveness depending on job seniority. Methods: The study included 420 teachers who participated in a complex vocal prophylactic and rehabilitation program carried out during a 24-day stay at a health resort hospital. Employment time varied from 4 to 45 years (mean 28.3 years). The participants were divided into three groups: employment time < 21 years (57 teachers), 21–30 years (182 teachers) and > 30 years (181 teachers). All of the subjects underwent maximum phonation time assessment as well as jitter, shimmer and NHR (noise to harmonic ratio) parameters assessment before and after the program; they also underwent perceptual evaluation using the GRBAS scale and voice self-assessment using the VHI-30 scale. Results: The perceptual evaluation using the GRBAS scale and self-report measures of voice function assessed using the VHI scale revealed improvement (p < 0.001). The parameters of jitter, shimmer and NHR improved significantly: jitter p < 0.001, shimmer p < 0.001 and NHR p < 0.003. Maximum phonation time increased slightly but significantly (p < 0.001). For all of the studied groups regardless of their employment time, maximum phonation time increased (p < 0.001). Initially, the lowest values of maximum phonation time were observed in teachers with longer job seniority, which improved after the rehabilitation but remained <15 s. Conclusions: Voice care for teachers is crucial regardless of their job seniority. Early prophylaxis for voice disorders is effective, as the results of rehabilitation are better in teachers with a shorter employment time.

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The Next 10 Years in Voice Evaluation and Treatment

Cited by 7 publications

References 66 publications

A dataset of laryngeal endoscopic images with comparative study on convolution neural network-based semantic segmentation

A dataset of laryngeal endoscopic images with comparative study on convolution neural network-based semantic segmentation

The teachers’ voice rehabilitation in sanatorium conditions

The Effectiveness of Rehabilitation of Occupational Voice Disorders in a Health Resort Hospital Environment

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