شماره ركورد كنفرانس :
144
عنوان مقاله :
Retinal Vessel Segmentation Using Non-Subsampled Contourlet Transform and Multi-Scale Line Detection
پديدآورندگان :
Masooomi Razie نويسنده , Ahmadifard Alireza نويسنده , Mohtadizadeh Ali نويسنده
كليدواژه :
component , Retinal images , Vessel segmentation , Contourlet Transform , Line detection
عنوان كنفرانس :
مجموعه مقالات دوازدهمين كنفرانس سيستم هاي هوشمند ايران
چكيده فارسي :
We present an effective method for automatically
extracting blood vessels from colour images of retinal. The
proposed method is based on non_subsampled contourlet
transform (NSCT) and line detectors. In the first step we enhance
green channel of retinal image by using the non-subsampled
contourlet transform at five levels and 25 directions. This process
improves discriminating vessels from background. In the next
step we use a line detector at eight scales and twelve directions to
extract proper features for detecting vessel centerlines. Finally,
vessel width is measured at each pixel on a vessel centerline. The
proposed method is evaluated and compared with several recent
methods using images from the DRIVE database. As reported the
performance of this method is very promising
شماره مدرك كنفرانس :
3817034