7986

7421

كارشناسي ارشد

مخابرات

اصفهان: دانشگاه صنعتي اصفهان، دانشكده برق و كامپيوتر

1391

نه،145ص.: مصور،جدول،نمودار

ص.ع.به فارسي و انگليسي

علي محمد دوست حسيني، سعيد صدري

حسين رباني

7/7/92

مهندسي برق و كامپيوتر

ID7421

به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي

146 Vessel Extration from Fundus Fluorescein Angiogram Based on Hessian Analysis of Directional Curvelet Subbands Asieh Soltanipour a soltanipour@ec iut ac ir Date of Submission 2013 Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Persian Supervisor Dr Saeed Sadri sadri@cc iut ac ir Dr Hossein Rabbani h rabbani@med mui ac ir Dr Mohammad Ali Doust Hosseini alimdh@cc iut ac ir Abstract Detection and localization of main structures in the retinal images like blood vessels and Optic Disk OD play important role in diagnosis of some diseases like Diabetic Retinopathy DR This paper presents a new procedure for automatic extraction of the blood vessels and of the OD in Fundus Fluorescein Angiogram FFA The algorithm of vessel extraction starts with the analysis of directional images resulting from sub bands of curvelet transform in the similar direction and different scales in order to extract blood vessel centerlines The final vessel segmentation is obtained using a simple region growing algorithm iteratively which uses the images resulting from morphological bit plane slicing as aggregated image and vessel centerlines as seeds Also the proposed algorithm for OD boundary extraction contains the following stages At first stage the FFA images are processed by a sequence of the dilation and erosion operators using multi structuring elements in order to remove blood vessels from the FFA images At second stage Fast Discreet Curvelet Transform FDCT of the image resulting from the previous step is calculated and curvelet coefficients are modified using an exponential function Then the image reconstructed from modified curvelet coefficients are used to extract OD regions candidate by applying canny edge detector and morphological operators At third stage the information of the blood vessels surrounding the OD region is used for extracting actual location of OD For this purpose the proposed method for detecting vessels is used for getting information of vessels around OD candidate regions Finally OD boundary is detected by applying distance regularized level set evolution DRLSE The proposed method for vessel extraction is tested on the FFA images from angiography unit of Isfahan Feiz hospital containing 70 FFA images from different DR stages and on the color images of DRIVE database The experimental results show accuracy more than 93 and 94 on FFA and color images respectively Also the proposed method for OD boundary extraction is tested on the FFA images from the angiography unit of Isfahan Feiz hospital The performance of propsed method shows accuracy more than 90 Keywords Fundus Fluorescein Angiography Curvelet Transform Distance Regularized Level Set Evolution DRLSE PDF created with pdfFactory trial version www pdffactory com

علي محمد دوست حسيني، سعيد صدري

حسين رباني