A Hybrid Unsupervised Approach for Retinal Vessel Segmentation.
Retinal vessel segmentation (RVS) is a significant source of useful information for monitoring, identification, initial medication, and surgical development of ophthalmic disorders. Most common disorders, i.e., stroke, diabetic retinopathy (DR), and cardiac diseases, often change the normal structur...
| Publicado en: | BioMed Research International pp. 1 - 21 |
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| Autores principales: | , , , |
| Formato: | computer program equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
12/16/2020
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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=147640820&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 147640820 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 12/16/2020 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 147640820 147640820 147640820 10.1155/2020/8365783 147640820 ppf: 1 ppct: 20 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A Hybrid Unsupervised Approach for Retinal Vessel Segmentation. aug: au: Khan, Khan Bahadar Siddique, Muhammad Shahbaz Ahmad, Muhammad Mazzara, Manuel affil: Department of Telecommunication Engineering, Faculty of Engineering, The Islamia University of Bahawalpur, Bahawalpur, Pakistan sug: subj: Retina Blood Supply Blood Vessels Anatomy and Histology Conceptual Framework Retina Radiography Eye Diseases Physiopathology Retina Anatomy and Histology Image Processing, Computer Assisted Human ab: Retinal vessel segmentation (RVS) is a significant source of useful information for monitoring, identification, initial medication, and surgical development of ophthalmic disorders. Most common disorders, i.e., stroke, diabetic retinopathy (DR), and cardiac diseases, often change the normal structure of the retinal vascular network. A lot of research has been committed to building an automatic RVS system. But, it is still an open issue. In this article, a framework is recommended for RVS with fast execution and competing outcomes. An initial binary image is obtained by the application of the MISODATA on the preprocessed image. For vessel structure enhancement, B-COSFIRE filters are utilized along with thresholding to obtain another binary image. These two binary images are combined by logical AND-type operation. Then, it is fused with the enhanced image of B-COSFIRE filters followed by thresholding to obtain the vessel location map (VLM). The methodology is verified on four different datasets: DRIVE, STARE, HRF, and CHASE_DB1, which are publicly accessible for benchmarking and validation. The obtained results are compared with the existing competing methods. pubtype: Academic Journal doctype: computer program equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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