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2020 2
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Improved U-Net based on ResNet and SE-Net with dual attention mechanism for glottis semantic segmentation.
Ni JC, Lee SH, Shen YC, Yang CS. Ni JC, et al. Med Eng Phys. 2025 Feb;136:104298. doi: 10.1016/j.medengphy.2025.104298. Epub 2025 Feb 6. Med Eng Phys. 2025. PMID: 39979012
The proposed model achieved positive results in predicting the scores on the public benchmark for automatic glottis segmentation (BAGLS) dataset....
The proposed model achieved positive results in predicting the scores on the public benchmark for automatic glottis segmentation (BAGLS …
Comparison of Deep Learning Models for Voice Disorder Classification Using Kymographic Images.
Panchami B, Kumar SP. Panchami B, et al. J Voice. 2025 Feb 12:S0892-1997(25)00001-3. doi: 10.1016/j.jvoice.2025.01.001. Online ahead of print. J Voice. 2025. PMID: 39947969
We used high-speed recordings from the Benchmark for Automatic Glottis Segmentation (BAGLS) dataset to generate kymographic images, which were then used for binary and tertiary classifications employing deep learning models. ...
We used high-speed recordings from the Benchmark for Automatic Glottis Segmentation (BAGLS) dataset to generate kymographic images, w …
Re-Training of Convolutional Neural Networks for Glottis Segmentation in Endoscopic High-Speed Videos.
Döllinger M, Schraut T, Henrich LA, Chhetri D, Echternach M, Johnson AM, Kunduk M, Maryn Y, Patel RR, Samlan R, Semmler M, Schützenberger A. Döllinger M, et al. Appl Sci (Basel). 2022 Oct;12(19):9791. doi: 10.3390/app12199791. Epub 2022 Sep 28. Appl Sci (Basel). 2022. PMID: 37583544 Free PMC article.
We propose and discuss several re-training approaches for convolutional neural networks (CNN) being used for HSV image segmentation. Our baseline CNN was trained on the BAGLS data set (58,750 images). The new BAGLS-RT data set consists of additional 21,050 images fr …
We propose and discuss several re-training approaches for convolutional neural networks (CNN) being used for HSV image segmentation. Our bas …
GlottisNetV2: Temporal Glottal Midline Detection Using Deep Convolutional Neural Networks.
Kruse E, Dollinger M, Schutzenberger A, Kist AM. Kruse E, et al. IEEE J Transl Eng Health Med. 2023 Jan 19;11:137-144. doi: 10.1109/JTEHM.2023.3237859. eCollection 2023. IEEE J Transl Eng Health Med. 2023. PMID: 36816097 Free PMC article.
Neural networks were set up in TensorFlow/Keras and trained and evaluated with the BAGLS dataset. We found that a dual decoder deep neural network termed GlottisNetV2 outperforms the previously proposed GlottisNet in terms of MAPE on the test dataset (1.85% to 6.3%) while …
Neural networks were set up in TensorFlow/Keras and trained and evaluated with the BAGLS dataset. We found that a dual decoder deep n …
Rethinking glottal midline detection.
Kist AM, Zilker J, Gómez P, Schützenberger A, Döllinger M. Kist AM, et al. Sci Rep. 2020 Nov 26;10(1):20723. doi: 10.1038/s41598-020-77216-6. Sci Rep. 2020. PMID: 33244031 Free PMC article.
We used a biophysical model to simulate different vocal fold oscillations, extended the openly available BAGLS dataset using manual annotations, utilized both, simulations and annotated endoscopic images, to train deep neural networks at different stages of the analysis wo …
We used a biophysical model to simulate different vocal fold oscillations, extended the openly available BAGLS dataset using manual a …
BAGLS, a multihospital Benchmark for Automatic Glottis Segmentation.
Gómez P, Kist AM, Schlegel P, Berry DA, Chhetri DK, Dürr S, Echternach M, Johnson AM, Kniesburges S, Kunduk M, Maryn Y, Schützenberger A, Verguts M, Döllinger M. Gómez P, et al. Sci Data. 2020 Jun 19;7(1):186. doi: 10.1038/s41597-020-0526-3. Sci Data. 2020. PMID: 32561845 Free PMC article.
In an international collaboration of researchers from seven institutions from the EU and USA, we have created BAGLS, a large, multihospital dataset of 59,250 high-speed videoendoscopy frames with individually annotated segmentation masks. The frames are based on 640 record …
In an international collaboration of researchers from seven institutions from the EU and USA, we have created BAGLS, a large, multiho …