Title :
Multiscale analysis revisited: Detection of drusen and vessel in digital retinal images
Author :
Zheng, Yuanjie ; Wang, Hongzhi ; Wu, Jue ; Gao, Jianbin ; Gee, James C.
Author_Institution :
Dept. of Radiol., Univ. of Pennsylvania, Philadelphia, PA, USA
fDate :
March 30 2011-April 2 2011
Abstract :
In order to more accurately detect drusen and vessel from retinal fundus images, we proposed a set of new features and presented a learning based detection scheme. These features are designed to describe the variation patterns of image´s local geometrical structure across various scales. Theoretical analysis and a series of preliminary experimental results demonstrate the extra ability and high accuracy of these features in distinguishing drusen and vessel from the background.
Keywords :
blood vessels; eye; medical image processing; digital retinal images; drusen detection; image local geometrical structure; learning based detection scheme; multiscale analysis; vessel detection; Accuracy; Biomedical imaging; Eigenvalues and eigenfunctions; Feature extraction; Image color analysis; Retina; Testing;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4244-4127-3
Electronic_ISBN :
1945-7928
DOI :
10.1109/ISBI.2011.5872500