Opto-Electronic Engineering, Volume. 51, Issue 7, 240114(2024)
Super-resolution reconstruction of retinal OCT image using multi-teacher knowledge distillation network
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
Category: Article
Received: May. 15, 2024
Accepted: Aug. 9, 2024
Published Online: Nov. 12, 2024
The Author Email: Chen Minghui (陈明惠)