Optic disc detection in retinal fundus images using gravitational law-based edge detection.
Diabetic retinopathy is one of the primary causes of vision loss worldwide. Early detection of the condition is critical for providing adequate treatment of this ailment to prevent vision loss. This detection is achieved by processing retinal fundus images. A key step in detecting diabetic retinopat...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 55; no. 6; pp. 935 - 949 |
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| Autores principales: | , , , |
| Formato: | review Journal Article |
| Publicado: |
Springer Nature
Jun2017
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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=123190316&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 123190316 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Jun2017 vid: 55 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 123190316 123190316 144064749 NLM27638111 123190316 10.1007/s11517-016-1563-0 NLM27638111 123190316 ppf: 935 ppct: 14 formats: fmt: @attributes: type: P tig: atl: Optic disc detection in retinal fundus images using gravitational law-based edge detection. aug: au: Alshayeji, Mohammad Al-Roomi, Suood Abed, Sa'ed Al-Roomi, Suood Abdulaziz affil: Computer Engineering Department, College of Computing Sciences and Engineering , Kuwait University , Kuwait City Kuwait sug: subj: Diabetic Retinopathy Diagnosis Diabetic Retinopathy Physiopathology Optic Nerve Physiopathology Algorithms Image Interpretation, Computer Assisted Methods Retina Interview Guides ab: Diabetic retinopathy is one of the primary causes of vision loss worldwide. Early detection of the condition is critical for providing adequate treatment of this ailment to prevent vision loss. This detection is achieved by processing retinal fundus images. A key step in detecting diabetic retinopathy is identifying the optic disc in these images. The optic disc is similar in color and contrast to the exudates that indicate diabetic retinopathy. Hence, the optic disc has to be removed from the fundus image before exudates can be detected. Detecting the optic disc is also required in algorithms used for blood vessel segmentation in fundus images. Therefore, there is a need for approaches that accurately and quickly detect optic disc. This paper proposes a simple, deterministic, and time-efficient approach for optic disc detection by adapting an edge detection algorithm inspired by the gravitational law. Our method introduces novel pre- and post-detection steps that aim to increase the accuracy of the adapted detection method. In addition, a candidate selection technique is proposed to decrease the number of missed optic discs. The proposed methodology was found to have a detection rate of 100, 97.75, 92.90, and 95 % for DRIVE, DiaRet, DMED, and STARE datasets, respectively, which is comparatively better than existing optic disc detection schemes. Experimental results showed an average running time of 0.40 s per image, which is significantly lower than available methods published in the literature. pubtype: Academic Journal doctype: review Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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