DMINet: A lightweight dual-mixed channel-independent network for cataract recognition

Xiao Wu, Yu Chen, Qiuyang Yan, Yuhang Zhao, Jilu Zhao, Xiaoqing Zhang, Risa Higashita, Jiang Liu

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review


Cataracts are the leading cause of visual impairment and blindness globally attracting abroad attention from society. Over the years researchers have developed many state-of-the-art convolutional neural networks (CNNs) to recognize cataract severity levels based on different ophthalmic images. However most current works focus on improving cataract recognition performance by designing complex CNNs often ignoring resource-constrained medical device limitations. To this problem this paper proposes a novel dual-mixed channel-independent convolution (DMIConv) method which takes advantage of the multiscale convolution kernels by combining a depthwise convolution with a depthwise dilated convolution sequentially. Moreover we build a lightweight dual-mixed channel-independent network (DMINet) to recognize cataracts. To verify the effectiveness and efficiency of DMINet we conduct extensive experiments on a clinical anterior segment optical coherence tomography (AS-OCT) dataset of nuclear cataract (NC) and a publicly available OCT dataset. The results show that our proposed DMINet keeps a better tradeoff between the model complexity and the classification performance than efficient CNNs e.g DMINet outperforms MixNet by 3.34% of accuracy by using 4.58

Original languageEnglish
Title of host publicationIJCNN 2023 - International Joint Conference on Neural Networks, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665488679
Publication statusPublished - 2023
Externally publishedYes
Event2023 International Joint Conference on Neural Networks, IJCNN 2023 - Gold Coast, Australia
Duration: 18 Jun 202323 Jun 2023

Publication series

NameProceedings of the International Joint Conference on Neural Networks


Conference2023 International Joint Conference on Neural Networks, IJCNN 2023
CityGold Coast


  • cataract
  • classification
  • convolution
  • DMIConv
  • lightweight

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence


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