Opto-Electronic Engineering, Volume. 51, Issue 7, 240114(2024)

Super-resolution reconstruction of retinal OCT image using multi-teacher knowledge distillation network

Minghui Chen1,*... Yanqi Lu1, Wenyi Yang1, Yuanzhu Wang2 and Yi Shao3 |Show fewer author(s)
Author Affiliations
  • 1Shanghai Engineering Research Center of Interventional Medical, Shanghai Institute for Interventional Medical Devices, School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
  • 2Shanghai Raykeen Laser Technology Co., Ltd., Shanghai 200120, China
  • 3Shanghai General Hospital, Shanghai 200080, China
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    Optical coherence tomography (OCT) is widely used in ophthalmic diagnosis and adjuvant therapy, but its imaging quality is inevitably affected by speckle noise and motion artifacts. This article proposes a multi teacher knowledge distillation network MK-OCT for OCT super-resolution tasks, which uses teacher networks with different advantages to train balanced, lightweight, and efficient student networks. The use of efficient channel distillation method ECD in MK-OCT also enables the model to better preserve the texture information of retinal images, meeting clinical needs. The experimental results show that compared with classical super-resolution networks, the model proposed in this paper performs well in both reconstruction accuracy and perceptual quality, with smaller model size and less computational complexity.

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    Minghui Chen, Yanqi Lu, Wenyi Yang, Yuanzhu Wang, Yi Shao. Super-resolution reconstruction of retinal OCT image using multi-teacher knowledge distillation network[J]. Opto-Electronic Engineering, 2024, 51(7): 240114

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    Paper Information

    Category: Article

    Received: May. 15, 2024

    Accepted: Aug. 9, 2024

    Published Online: Nov. 12, 2024

    The Author Email: Chen Minghui (陈明惠)

    DOI:10.12086/oee.2024.240114

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