Fully Automated Robust System to Detect Retinal Edema, Central Serous Chorioretinopathy, and Age Related Macular Degeneration from Optical Coherence Tomography Images.

Maculopathy is the excessive damage to macula that leads to blindness. It mostly occurs due to retinal edema (RE), central serous chorioretinopathy (CSCR), or age related macular degeneration (ARMD). Optical coherence tomography (OCT) imaging is the latest eye testing technique that can detect these...

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Publicado en:BioMed Research International Vol. 2017; pp. 1 - 16
Autores principales: Khalid, Samina, Akram, M. Usman, Hassan, Taimur, Nasim, Ammara, Jameel, Amina
Formato: equations & formulas pictorial research tables/charts Journal Article
Publicado: Wiley-Blackwell 3/23/2017
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 3/23/2017
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2017/7148245
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        atl: Fully Automated Robust System to Detect Retinal Edema, Central Serous Chorioretinopathy, and Age Related Macular Degeneration from Optical Coherence Tomography Images.
      aug:
        au:
          Khalid, Samina
          Akram, M. Usman
          Hassan, Taimur
          Nasim, Ammara
          Jameel, Amina
        affil: Department of Computer Science & Information Technology, Mirpur University of Science and Technology, Mirpur, Pakistan
      sug:
        subj:
          Macular Degeneration Diagnosis
          Tomography, Optical Coherence
          Decision Support Systems, Clinical
          Retinal Diseases Diagnosis
          Human
          Sensitivity and Specificity
          Descriptive Statistics
          Data Analysis Software
      ab: Maculopathy is the excessive damage to macula that leads to blindness. It mostly occurs due to retinal edema (RE), central serous chorioretinopathy (CSCR), or age related macular degeneration (ARMD). Optical coherence tomography (OCT) imaging is the latest eye testing technique that can detect these syndromes in early stages. Many researchers have used OCT images to detect retinal abnormalities. However, to the best of our knowledge, no research that presents a fully automated system to detect all of these macular syndromes is reported. This paper presents the world’s first ever decision support system to automatically detect RE, CSCR, and ARMD retinal pathologies and healthy retina from OCT images. The automated disease diagnosis in our proposed system is based on multilayered support vector machines (SVM) classifier trained on 40 labeled OCT scans (10 healthy, 10 RE, 10 CSCR, and 10 ARMD). After training, SVM forms an accurate decision about the type of retinal pathology using 9 extracted features. We have tested our proposed system on 2819 OCT scans (1437 healthy, 640 RE, and 742 CSCR) of 502 patients from two different datasets and our proposed system correctly diagnosed 2817/2819 subjects with the accuracy, sensitivity, and specificity ratings of 99.92%, 100%, and 99.86%, respectively.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        pictorial
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        Journal Article
      ougenre: Article
    language: English
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