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

• URL: http://arxiv.org/abs/2404.11525v3
• Date: Sun, 28 Jul 2024 18:53:18 GMT
• Title: JointViT: Modeling Oxygen Saturation Levels with Joint Supervision on Long-Tailed OCTA
• Abstract summary: We propose JointViT, a novel model based on the Vision Transformer architecture, incorporating a joint loss function for supervision. We introduce a balancing augmentation technique during data preprocessing to improve the model's performance. Our proposed method significantly outperforms other state-of-the-art methods, achieving improvements of up to 12.28% in overall accuracy.
• Score: 5.935281996910959
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 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. See project website https://steve-zeyu-zhang.github.io/JointViT

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