• DocumentCode
    2458834
  • Title

    Development of primary glaucoma classification technique using optic cup & disc ratio

  • Author

    Patil, Dnyaneshwari D. ; Manza, Ramesh R. ; Bedke, Gangadevi C. ; Rathod, Dipali D.

  • Author_Institution
    Dept. of CS & IT, Dr. B.A.M. Univ., Aurangabad, India
  • fYear
    2015
  • fDate
    8-10 Jan. 2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Glaucoma is Eye dieses & one of the leading causes of blindness worldwide. It is due to the increase in intra ocular pressure within the eyes. The detection and diagnosis of glaucoma is very important. Here we present an algorithm which works on two different data base for the same purpose to calculate optic cup to disc ratio. For this purpose we use DRIONS-DB high resolution fundus images. From these high resolution RGB images we are going from preprocessing to ROI extraction steps i.e. our optic disc & cup detection. For that purpose we use K-means clustering for detection & measure area of disc & cup then, calculate ratio. After calculating ratio we apply that same method on another database i.e. RIM-I 64 healthy images & we got healthy CDR between 0.2 to 0.6. By the combination of two data base DRIONS-DB & RIM-Il, overall 97% result is achieved.
  • Keywords
    diseases; eye; feature extraction; image classification; image resolution; medical image processing; pattern clustering; DRIONS-DB high resolution fundus images; K-means clustering; ROI extraction; high resolution RGB images; optic cup-disc ratio; primary glaucoma classification technique; Biomedical optical imaging; Databases; Histograms; Integrated optics; Optical imaging; Optical variables measurement; Retina; Cup to disc ratio (CDR); Glaucoma; K-means clustering; Region of interest (ROI);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pervasive Computing (ICPC), 2015 International Conference on
  • Conference_Location
    Pune
  • Type

    conf

  • DOI
    10.1109/PERVASIVE.2015.7087139
  • Filename
    7087139