Combination of Enhanced Depth Imaging Optical Coherence Tomography and Fundus Images for Glaucoma Screening.
Glaucoma is an eye disease that damages the optic nerve and can lead to irreversible loss of peripheral vision gradually and even blindness without treatment. Thus, diagnosing glaucoma in the early stage is essential for treatment. In this paper, an automatic method for early glaucoma screening is p...
| Publicado en: | Journal of Medical Systems Vol. 43; no. 6 |
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| Autores principales: | , , , , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jun2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=136503273&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 136503273 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Jun2019 vid: 43 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 136503273 136503273 136503273 10.1007/s10916-019-1303-8 136503273 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Combination of Enhanced Depth Imaging Optical Coherence Tomography and Fundus Images for Glaucoma Screening. aug: au: Chen, Zailiang Zheng, Xianxian Shen, Hailan Zeng, Ziyang Liu, Qing Li, Zhuo affil: School of Computer Science and Engineering, Central South University, 410083, Changsha, China sug: subj: Glaucoma Prevention and Control Tomography, Optical Coherence Methods Radiographic Image Enhancement Eye Radiography Automation Health Screening Methods Early Diagnosis Methods Eye Anatomy and Histology Eye Physiopathology Glaucoma Diagnosis Health Personnel Education Funding Source Image Processing, Computer Assisted Optic Nerve Anatomy and Histology Optic Nerve Physiopathology Glaucoma Classification Human Comparative Studies ab: Glaucoma is an eye disease that damages the optic nerve and can lead to irreversible loss of peripheral vision gradually and even blindness without treatment. Thus, diagnosing glaucoma in the early stage is essential for treatment. In this paper, an automatic method for early glaucoma screening is proposed. The proposed method combines structural parameters and textural features extracted from enhanced depth imaging optical coherence tomography (EDI-OCT) images and fundus images. The method first segments anterior the lamina cribrosa surface (ALCS) based on region-aware strategy and residual U-Net and then extracts structural features of the lamina cribrosa, such as lamina cribrosa depth and deformation of lamina cribrosa. In fundus images, scanning lines based on disc center and brightness reduction are used for optic disc segmentation and brightness compensation is utilized for segmenting the optic cup. Afterward, the cup-to-disc ratio (CDR) and textural features are extracted from fundus images. Hybrid features are used for training and classification to screen glaucoma by gcForest in the early stage. The proposed method has given exceptional results with 96.88% accuracy and 91.67% sensitivity. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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