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[MIUA 2024 Oral] JointViT: Modeling Oxygen Saturation Levels with Joint Supervision on Long-Tailed OCTA

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JointViT: Modeling Oxygen Saturation Levels with Joint Supervision on Long-Tailed OCTA
MIUA 2024 Oral

Zeyu Zhang, Xuyin Qi, Mingxi Chen, Guangxi Li, Ryan Pham, Ayub Qassim, Ella Berry, Zhibin Liao, Owen Siggs, Robert Mclaughlin, Jamie Craig, Minh-Son To

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The oxygen saturation level in the blood (SaO2) is crucial for health, particularly in relation to sleep-related breathing disorders. However, continuous monitoring of SaO2 is time-consuming and highly variable depending on patients' conditions. Recently, optical coherence tomography angiography (OCTA) has shown promising development in rapidly and effectively screening eye-related lesions, offering the potential for diagnosing sleep-related disorders. To bridge this gap, our paper presents three key contributions. Firstly, we propose JointViT, a novel model based on the Vision Transformer architecture, incorporating a joint loss function for supervision. Secondly, we introduce a balancing augmentation technique during data preprocessing to improve the model's performance, particularly on the long-tail distribution within the OCTA dataset. Lastly, through comprehensive experiments on the OCTA dataset, our proposed method significantly outperforms other state-of-the-art methods, achieving improvements of up to 12.28% in overall accuracy. This advancement lays the groundwork for the future utilization of OCTA in diagnosing sleep-related disorders.

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News

(06/18/2024) 🎉 Our paper has been selected as an oral presentation at MIUA 2024!

(05/14/2024) 🎉 Our paper has been accepted to MIUA 2024!

Code coming soon!

Citation

@inproceedings{zhang2024jointvit,
  title={Jointvit: Modeling oxygen saturation levels with joint supervision on long-tailed octa},
  author={Zhang, Zeyu and Qi, Xuyin and Chen, Mingxi and Li, Guangxi and Pham, Ryan and Qassim, Ayub and Berry, Ella and Liao, Zhibin and Siggs, Owen and Mclaughlin, Robert and others},
  booktitle={Annual Conference on Medical Image Understanding and Analysis},
  pages={158--172},
  year={2024},
  organization={Springer}
}