Segmentation of Retinal Blood Vessels using Sub-blocking and Weighted Sum Method

Notice: Undefined variable: link_article in /home/ijtc/public_html/plugins/content/bt_socialshare/bt_socialshare.php on line 818

Notice: Undefined property: stdClass::$image in /home/ijtc/public_html/plugins/content/bt_socialshare/bt_socialshare.php on line 818

Notice: Undefined variable: title in /home/ijtc/public_html/plugins/content/bt_socialshare/bt_socialshare.php on line 818

Notice: Undefined offset: 1 in /home/ijtc/public_html/plugins/content/bt_socialshare/bt_socialshare.php on line 820
File Size:
1.70 MB
Volume 3, Issue 7 (July, 2017)
Publication No:
Ankit Anand, Er. Sukhpreet Kaur

Notice: Undefined variable: pdFileDate in /home/ijtc/public_html/components/com_phocadownload/views/file/tmpl/default.php on line 277
2 x

There are various eye diseases in the patients suffering from the diabetes which includes Diabetic retinopathy, Glaucoma, Hypertension etc. These all are the most common sight threatening eye diseases due to the changes in the blood vessel structure. The proposed method using supervised methods concluded that the segmentation of the retinal blood vessels can be performed accurately using neural networks training. It uses features which includes gray level features, moment invariant based features, Gabor filtering, intensity feature, vesselness feature for feature vector computation. Then the feature vector is calculated using only the prominent features.

Retinal blood vessel segmentation, Diabetic Retinopathy, Neural Network, Feature Vector.