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Unsupervised Segmentation of Bolus and Residue in Videofluoroscopy Swallowing Studies.

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第一作者： Farnaz,Khodami

第一单位： Faculty of Electrical and Computer Engineering, University of Toronto, 10 King's College Rd, Toronto, ON M5S 1A1, Canada.

作者： Farnaz,Khodami ^[1] ; Mehdy,Dousty ^[2] ; James L,Coyle ^[3] ; Ervin,Sejdić ^[4]

作者单位： Faculty of Electrical and Computer Engineering, University of Toronto, 10 King's College Rd, Toronto, ON M5S 1A1, Canada. ^[1] Faculty of Electrical and Computer Engineering, University of Toronto, 10 King's College Rd, Toronto, ON M5S 1A1, Canada.;Vector Institute, 108 College St, Toronto, ON M5G 0C6, Canada. ^[2] School of Health and Rehabilitation Sciences, University of Pittsburgh, Forbes Tower, 3600 Atwood St, Pittsburgh, PA 15260, USA. ^[3] Faculty of Electrical and Computer Engineering, University of Toronto, 10 King's College Rd, Toronto, ON M5S 1A1, Canada.;North York General Hospital, 4001 Leslie St, North York, ON M2K 1E1, Canada. ^[4]

关键词 autoencoder bolus tracking convolutional neural network dysphagia machine learning positional encoding residue detection unsupervised learning unsupervised segmentation videofluoroscopy swallowing study

DOI 10.3390/jimaging11100368

PMID 41150044

发布时间 2025-10-31

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Journal of imaging

2025年11卷10期

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Journal of imaging

2025年11卷10期

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Unsupervised Segmentation of Bolus and Residue in Videofluoroscopy Swallowing Studies.

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Unsupervised Segmentation of Bolus and Residue in Videofluoroscopy Swallowing Studies.

Journal of imaging

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Journal of imaging

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