title: Automated extraction of retinal vasculature.
abstract: OBJECTIVE
  The authors propose an algorithm that automatically extracts retinal vasculature and provides a simple measure to correct the extraction. The output of the method is a network of salient points, and blood vessels are drawn by connecting the salient points using a centripetal parameterized Catmull-Rom spline.
  
  
  METHODS
  The algorithm starts by background correction. The corrected image is filtered with a bank of Gabor kernels, and the responses are consolidated to form a maximal image. After that, the maximal image is thinned to get a network of 1-pixel lines, analyzed and pruned to locate forks and form branches. Finally, the Ramer-Douglas-Peucker algorithm is used to determine salient points. When extraction is not satisfactory, the user simply shifts the salient points to edit the segmentation.
  
  
  RESULTS
  On average, the authors' extractions cover 93% of ground truths (on the Drive database).
  
  
  CONCLUSIONS
  By expressing retinal vasculature as a series of connected points, the proposed algorithm not only provides a means to edit segmentation but also gives knowledge of the shape of the blood vessels and their connections.
authors.affiliation: Department of Electronic and Computer Engineering, Ngee Ann Polytechnic, Singapore 599489.
authors.forename: Jen Hong
authors.initials: JH
authors.lastname: Tan
authors.affiliation: Department of Electronic and Computer Engineering, Ngee Ann Polytechnic, Singapore 599489 and Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia.
authors.forename: U Rajendra
authors.initials: UR
authors.lastname: Acharya
authors.affiliation: Department of Electronic and Computer Engineering, Ngee Ann Polytechnic, Singapore 599489.
authors.forename: Kuang Chua
authors.initials: KC
authors.lastname: Chua
authors.affiliation: Algo Access, Singapore 120434.
authors.forename: Calvin
authors.initials: C
authors.lastname: Cheng
authors.affiliation: National Healthcare Group Eye Institute, Tan Tock Seng Hospital, Singapore 308433.
authors.forename: Augustinus
authors.initials: A
authors.lastname: Laude
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000792:Angiography / Q000379:methods*; D003920:Diabetes Mellitus / Q000000981:diagnostic imaging; D003941:Diagnostic Techniques, Ophthalmological; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D012171:Retinal Vessels / Q000000981:diagnostic imaging*