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A Feasibility Study on Image Inpainting for Non-Cleft Lip Generation from Patients with Cleft Lip

Shuang Chen, Amir Atapour-Abarghouei, Jane Kerby, Edmond S. L. Ho, David C. G. Sainsbury, Sophie Butterworth and Hubert P. H. Shum
Proceedings of the 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), 2022

 Oral Presentation

A Feasibility Study on Image Inpainting for Non-Cleft Lip Generation from Patients with Cleft Lip

Abstract

A Cleft lip is a congenital abnormality requiring surgical repair by a specialist. The surgeon must have extensive experience and theoretical knowledge to perform surgery, and Artificial Intelligence (AI) method has been proposed to guide surgeons in improving surgical outcomes. If AI can be used to predict what a repaired cleft lip would look like, surgeons could use it as an adjunct to adjust their surgical technique and improve results. To explore the feasibility of this idea while protecting patient privacy, we propose a deep learning-based image inpainting method that is capable of covering a cleft lip and generating a lip and nose without a cleft. Our experiments are conducted on two real-world cleft lip datasets and are assessed by expert cleft lip surgeons to demonstrate the feasibility of the proposed method

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Citations

BibTeX

@inproceedings{chen22feasibility,
 author={Chen, Shuang and Atapour-Abarghouei, Amir and Kerby, Jane and Ho, Edmond S. L. and Sainsbury, David C. G. and Butterworth, Sophie and Shum, Hubert P. H.},
 booktitle={Proceedings of the 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics},
 series={BHI '22},
 title={A Feasibility Study on Image Inpainting for Non-Cleft Lip Generation from Patients with Cleft Lip},
 year={2022},
 month={9},
 pages={1--4},
 numpages={4},
 doi={10.1109/BHI56158.2022.9926917},
 publisher={IEEE},
 location={Ioannina, Greece},
}

RIS

TY  - CONF
AU  - Chen, Shuang
AU  - Atapour-Abarghouei, Amir
AU  - Kerby, Jane
AU  - Ho, Edmond S. L.
AU  - Sainsbury, David C. G.
AU  - Butterworth, Sophie
AU  - Shum, Hubert P. H.
T2  - Proceedings of the 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics
TI  - A Feasibility Study on Image Inpainting for Non-Cleft Lip Generation from Patients with Cleft Lip
PY  - 2022
Y1  - 9 2022
SP  - 1
EP  - 4
DO  - 10.1109/BHI56158.2022.9926917
PB  - IEEE
ER  - 

Plain Text

Shuang Chen, Amir Atapour-Abarghouei, Jane Kerby, Edmond S. L. Ho, David C. G. Sainsbury, Sophie Butterworth and Hubert P. H. Shum, "A Feasibility Study on Image Inpainting for Non-Cleft Lip Generation from Patients with Cleft Lip," in BHI '22: Proceedings of the 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics, pp. 1-4, Ioannina, Greece, IEEE, Sep 2022.

Supporting Grants

Similar Research

Shuang Chen, Amir Atapour-Abarghouei, Edmond S. L. Ho and Hubert P. H. Shum, "INCLG: Inpainting for Non-Cleft Lip Generation with a Multi-Task Image Processing Network", Software Impacts (SIMPAC), 2023
Daniel Organisciak, Edmond S. L. Ho and Hubert P. H. Shum, "Makeup Style Transfer on Low-Quality Images with Weighted Multi-Scale Attention", Proceedings of the 2020 International Conference on Pattern Recognition (ICPR), 2020

 

 

Last updated on 24 February 2024
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