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
تعداد صفحه :
5
كليدواژه :
component , Retinal images , Vessel segmentation , Contourlet Transform , Line detection
عنوان كنفرانس :
مجموعه مقالات دوازدهمين كنفرانس سيستم هاي هوشمند ايران
زبان مدرك :
فارسی
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
سال انتشار :
2014
از صفحه :
1
تا صفحه :
5
سال انتشار :
0
لينک به اين مدرک :
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