research-article

Optic Disc Segmentation Based on Phase-fusion PSPNet

Authors:

MaoNian WuAuthors Info & Claims

ISAIMS '21: Proceedings of the 2nd International Symposium on Artificial Intelligence for Medicine Sciences

Pages 152 - 156

https://doi.org/10.1145/3500931.3500959

Published: 22 December 2021 Publication History

Abstract

In the analysis of fundus images, optic disc segmentation is vital to judge eye diseases such as diabetic retinopathy and glaucoma. Improving the accuracy of optic disc segmentation is of great significance to the diagnosis of the above diseases. Based on the PSPNet model, the Phase-Fusion PSPNet network structure is proposed. The network is connected to the phase upsampling module after the pyramid pooling module, which reduces information loss and makes the network suitable for segmentation tasks with fuzzy edges. The principle of phase upsampling module is to upsample the larger size span step by step and combine it with the corresponding size feature map. iChallenge-PM, iChallenge-AMD, and iChallenge-GON as the training and validation datasets in the paper. The IoU and PA of Phase-fusion PSPNet are 89.93% and 94.94%. Compared with PSPNet, the IoU and PA increased by 1.22% and 1.62% respectively. Experiments show that adding the phase upsampling module makes the model have a better segmentation performance.

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Cited By

Yang XZheng YMei CJiang GTian BWang L(2024)UGLS: an uncertainty guided deep learning strategy for accurate image segmentationFrontiers in Physiology10.3389/fphys.2024.136238615Online publication date: 8-Apr-2024
https://doi.org/10.3389/fphys.2024.1362386
Xiao YZhao JYu YDing XLiu SBao WWen SZhou X(2024)SimpleCNN-UNet: An optic disc image segmentation network based on efficient small-kernel convolutionsExpert Systems with Applications10.1016/j.eswa.2024.124935256(124935)Online publication date: Dec-2024
https://doi.org/10.1016/j.eswa.2024.124935
Zhao TGuan YTu DYuan LLu G(2023)Neighbored-attention U-net (NAU-net) for diabetic retinopathy image segmentationFrontiers in Medicine10.3389/fmed.2023.130979510Online publication date: 7-Dec-2023
https://doi.org/10.3389/fmed.2023.1309795
Show More Cited By

Index Terms

Optic Disc Segmentation Based on Phase-fusion PSPNet
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Image segmentation

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ISAIMS '21: Proceedings of the 2nd International Symposium on Artificial Intelligence for Medicine Sciences

October 2021

593 pages

ISBN:9781450395588

DOI:10.1145/3500931

Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 22 December 2021

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ISAIMS 2021

ISAIMS 2021: 2nd International Symposium on Artificial Intelligence for Medicine Sciences

October 29 - 31, 2021

Beijing, China

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Overall Acceptance Rate 53 of 112 submissions, 47%

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Cited By

Yang XZheng YMei CJiang GTian BWang L(2024)UGLS: an uncertainty guided deep learning strategy for accurate image segmentationFrontiers in Physiology10.3389/fphys.2024.136238615Online publication date: 8-Apr-2024
https://doi.org/10.3389/fphys.2024.1362386
Xiao YZhao JYu YDing XLiu SBao WWen SZhou X(2024)SimpleCNN-UNet: An optic disc image segmentation network based on efficient small-kernel convolutionsExpert Systems with Applications10.1016/j.eswa.2024.124935256(124935)Online publication date: Dec-2024
https://doi.org/10.1016/j.eswa.2024.124935
Zhao TGuan YTu DYuan LLu G(2023)Neighbored-attention U-net (NAU-net) for diabetic retinopathy image segmentationFrontiers in Medicine10.3389/fmed.2023.130979510Online publication date: 7-Dec-2023
https://doi.org/10.3389/fmed.2023.1309795
Zhang JMei CLi ZYing JZheng QYi QWang L(2023)Automated segmentation of optic disc and cup depicted on color fundus images using a distance-guided deep learning strategyBiomedical Signal Processing and Control10.1016/j.bspc.2023.10516386(105163)Online publication date: Sep-2023
https://doi.org/10.1016/j.bspc.2023.105163

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