Adaptive weighted locality-constrained sparse coding for glaucoma diagnosis.
Glaucoma is a sight-threading disease which can lead to irreversible blindness. Currently, extracting the vertical cup-to-disc ratio (CDR) from 2D retinal fundus images is promising for automatic glaucoma diagnosis. In this paper, we present a novel sparse coding approach for glaucoma diagnosis call...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 57; no. 9; pp. 2055 - 2068 |
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| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Sep2019
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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=138201477&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 138201477 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Sep2019 vid: 57 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 138201477 138201477 NLM31352661 10.1007/s11517-019-02011-z NLM31352661 138201477 ppf: 2055 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Adaptive weighted locality-constrained sparse coding for glaucoma diagnosis. aug: au: Zhou, Wei Yi, Yugen Bao, Jining Wang, Wenle affil: College of Computer Science, Shenyang Aerospace University, Shenyang, Liaoning, China sug: subj: Image Interpretation, Computer Assisted Methods Algorithms Glaucoma Retina Resource Databases Image Processing, Computer Assisted Methods Interview Guides Scales ab: Glaucoma is a sight-threading disease which can lead to irreversible blindness. Currently, extracting the vertical cup-to-disc ratio (CDR) from 2D retinal fundus images is promising for automatic glaucoma diagnosis. In this paper, we present a novel sparse coding approach for glaucoma diagnosis called adaptive weighted locality-constrained sparse coding (AWLCSC). Different from the existing reconstruction-based glaucoma diagnosis approaches, the weighted matrix in AWLCSC is constructed by adaptively fusing multiple distance measurement information between the reference images and the testing image, making our approach more robust and effective to glaucoma diagnosis. In our approach, the disc image is firstly extracted and reconstructed according to the proposed AWLCSC technique. Then, with the usage of the obtained reconstruction coefficients and a series of reference disc images with known CDRs, the CDR of the testing disc image can be automated estimation for glaucoma diagnosis. The performance of the proposed AWLCSC is evaluated on two publicly available DRISHTI-GS1 and RIM-ONE r2 databases. The experimental results indicate that the proposed approach outperforms the state-of-the-art approaches. Graphical abstract The flowchart of the proposed approach for glaucoma diagnosis. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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