Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/105468
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Computing | - |
dc.creator | Ali, R | - |
dc.creator | Sheng, B | - |
dc.creator | Li, P | - |
dc.creator | Chen, Y | - |
dc.creator | Li, H | - |
dc.creator | Yang, P | - |
dc.creator | Jung, Y | - |
dc.creator | Kim, J | - |
dc.creator | Chen, CLP | - |
dc.date.accessioned | 2024-04-15T07:34:33Z | - |
dc.date.available | 2024-04-15T07:34:33Z | - |
dc.identifier.issn | 1551-3203 | - |
dc.identifier.uri | http://hdl.handle.net/10397/105468 | - |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.rights | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
dc.rights | The following publication R. Ali et al., "Optic Disk and Cup Segmentation Through Fuzzy Broad Learning System for Glaucoma Screening," in IEEE Transactions on Industrial Informatics, vol. 17, no. 4, pp. 2476-2487, April 2021 is available at https://doi.org/10.1109/TII.2020.3000204. | en_US |
dc.subject | Broad learning system (BLS) | en_US |
dc.subject | Fuzzy system | en_US |
dc.subject | Neural networks | en_US |
dc.subject | Ocular disease | en_US |
dc.subject | Optic disk and cup | en_US |
dc.subject | Segmentation | en_US |
dc.title | Optic disk and cup segmentation through fuzzy broad learning system for glaucoma screening | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 2476 | - |
dc.identifier.epage | 2487 | - |
dc.identifier.volume | 17 | - |
dc.identifier.issue | 4 | - |
dc.identifier.doi | 10.1109/TII.2020.3000204 | - |
dcterms.abstract | Glaucoma is an ocular disease that causes permanent blindness if not cured at an early stage. Cup-to-disk ratio (CDR), obtained by dividing the height of optic cup (OC) with the height of optic disk (OD), is a widely adopted metric used for glaucoma screening. Therefore, accurately segmenting OD and OC is crucial for calculating a CDR. Most methods have employed deep learning methods for the segmentation of OD and OC. However, these methods are very time consuming. In this article, we present a new fuzzy broad learning system-based technique for OD and OC segmentation with glaucoma screening. We comprehensively integrated extracting a region of interest from RGB images, data augmentation, extracting red and green channel images, and inputting them to the two separate fuzzy broad learning system-based neural networks for segmenting the OD and OC, respectively, and then calculated CDR. Experiments show that our fuzzy broad learning system-based technique outperforms many state-of-the-art methods. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | IEEE transactions on industrial informatics, Apr. 2021, v. 17, no. 4, p. 2476-2487 | - |
dcterms.isPartOf | IEEE transactions on industrial informatics | - |
dcterms.issued | 2021-04 | - |
dc.identifier.scopus | 2-s2.0-85099509453 | - |
dc.identifier.eissn | 1941-0050 | - |
dc.description.validate | 202402 bcch | - |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | COMP-0079 | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | National Natural Science Foundation of China; Science and Technology Commission of Shanghai Municipality; The Hong Kong Polytechnic University | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 43204275 | en_US |
dc.description.oaCategory | Green (AAM) | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Li_Optic_Disk_Cup.pdf | Pre-Published version | 6.29 MB | Adobe PDF | View/Open |
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