Title | Attention to region: Region-based integration-and-recalibration networks for nuclear cataract classification using AS-OCT images |
Author | |
Corresponding Author | Liu,Jiang |
Publication Years | 2022-08-01
|
DOI | |
Source Title | |
ISSN | 1361-8415
|
EISSN | 1361-8423
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Volume | 80 |
Abstract | Nuclear cataract (NC) is a leading eye disease for blindness and vision impairment globally. Accurate and objective NC grading/classification is essential for clinically early intervention and cataract surgery planning. Anterior segment optical coherence tomography (AS-OCT) images are capable of capturing the nucleus region clearly and measuring the opacity of NC quantitatively. Recently, clinical research has suggested that the opacity correlation and repeatability between NC severity levels and the average nucleus density on AS-OCT images is high with the interclass and intraclass analysis. Moreover, clinical research has suggested that opacity distribution is uneven on the nucleus region, indicating that the opacities from different nucleus regions may play different roles in NC diagnosis. Motivated by the clinical priors, this paper proposes a simple yet effective region-based integration-and-recalibration attention (RIR), which integrates multiple feature map region representations and recalibrates the weights of each region via softmax attention adaptively. This region recalibration strategy enables the network to focus on high contribution region representations and suppress less useful ones. We combine the RIR block with the residual block to form a Residual-RIR module, and then a sequence of Residual-RIR modules are stacked to a deep network named region-based integration-and-recalibration network (RIR-Net), to predict NC severity levels automatically. The experiments on a clinical AS-OCT image dataset and two OCT datasets demonstrate that our method outperforms strong baselines and previous state-of-the-art methods. Furthermore, attention weight visualization analysis and ablation studies verify the capability of our RIR-Net for adjusting the relative importance of different regions in feature maps dynamically, agreeing with the clinical research. |
Keywords | |
URL | [Source Record] |
Indexed By | |
Language | English
|
SUSTech Authorship | First
; Corresponding
|
EI Accession Number | 20222612280458
|
EI Keywords | Diagnosis
; Grading
; Image Classification
; Image Segmentation
; Integration
; Opacity
; Optical Tomography
|
ESI Classification Code | Medicine And Pharmacology:461.6
; Data Processing And Image Processing:723.2
; Light/Optics:741.1
; Optical Devices And Systems:741.3
; Calculus:921.2
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ESI Research Field | COMPUTER SCIENCE
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Scopus EID | 2-s2.0-85132723766
|
Data Source | Scopus
|
Citation statistics |
Cited Times [WOS]:3
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Document Type | Journal Article |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/356227 |
Department | Research Institute of Trustworthy Autonomous Systems 工学院_计算机科学与工程系 |
Affiliation | 1.Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China 2.Institute of High Performance Computing,Agency for Science,Technology and Research,138632,Singapore 3.Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,510060,China 4.Cixi Institute of Biomedical Engineering,Ningbo Institute of Materials Technology and Engineering,Chinese Academy of Sciences,Ningbo,315300,China 5.Tomey Corporation,Nagoya,4510051,Japan 6.Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation,Southern University of Science and Technology,Shenzhen,518055,China |
First Author Affilication | Research Institute of Trustworthy Autonomous Systems; Department of Computer Science and Engineering |
Corresponding Author Affilication | Research Institute of Trustworthy Autonomous Systems; Department of Computer Science and Engineering; Southern University of Science and Technology |
First Author's First Affilication | Research Institute of Trustworthy Autonomous Systems; Department of Computer Science and Engineering |
Recommended Citation GB/T 7714 |
Zhang,Xiaoqing,Xiao,Zunjie,Fu,Huazhu,et al. Attention to region: Region-based integration-and-recalibration networks for nuclear cataract classification using AS-OCT images[J]. MEDICAL IMAGE ANALYSIS,2022,80.
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APA |
Zhang,Xiaoqing.,Xiao,Zunjie.,Fu,Huazhu.,Hu,Yan.,Yuan,Jin.,...&Liu,Jiang.(2022).Attention to region: Region-based integration-and-recalibration networks for nuclear cataract classification using AS-OCT images.MEDICAL IMAGE ANALYSIS,80.
|
MLA |
Zhang,Xiaoqing,et al."Attention to region: Region-based integration-and-recalibration networks for nuclear cataract classification using AS-OCT images".MEDICAL IMAGE ANALYSIS 80(2022).
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