Hybrid multi-kernel SVM algorithm for detection of microaneurysm in color fundus images.
Diabetic retinopathy (DR) is a chronic disease that may cause vision loss in diabetic patients. Microaneurysms which are characterized by small red spots on the retina due to fluid or blood leakage from the weak capillary wall often occur during the early stage of DR, making screening at this stage...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 60; no. 5; pp. 1377 - 1391 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
May2022
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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=156318888&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 156318888 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: May2022 vid: 60 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 156318888 156318888 NLM35325369 10.1007/s11517-022-02534-y NLM35325369 156318888 ppf: 1377 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Hybrid multi-kernel SVM algorithm for detection of microaneurysm in color fundus images. aug: au: Derwin, D. Jeba Shan, B. Priestly Singh, O. Jeba affil: SRM TRP Engineering College, Tiruchirappalli, Tamil Nadu, India sug: subj: Diabetic Retinopathy Algorithms Retina ab: Diabetic retinopathy (DR) is a chronic disease that may cause vision loss in diabetic patients. Microaneurysms which are characterized by small red spots on the retina due to fluid or blood leakage from the weak capillary wall often occur during the early stage of DR, making screening at this stage is essential. In this paper, an automatic screening system for early detection of DR in retinal images is developed using a combined shape and texture features. Due to minimum number of hand-crafted features, the computational burden is much reduced. The proposed hybrid multi-kernel support vector machine classifier is constructed by learning a kernel model formed as a combination of the base kernels. This approach outperforms the recent deep learning techniques in terms of the evaluation metrics. The efficiency of the proposed scheme is experimentally validated on three public datasets - Retinopathy Online Challenge, DIARETdB1, MESSIDOR, and AGAR300 (developed for this study). Studies reveal that the proposed model produced the best results of 0.503 in ROC dataset, 0.481 in DIARETdB1, and 0.464 in the MESSIDOR dataset in terms of FROC score. The AGAR300 database outperforms the existing MA detection algorithm in terms of FROC, AUC, F1 score, precision, sensitivity, and specificity which guarantees the robustness of this system. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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