NDLI: Detecting false vessel recognitions in retinal fundus analysis

Content Provider	IEEE Xplore Digital Library
Author	Giani, A. Grisan, E. De Luca, M. Ruggeri, A.
Copyright Year	2006
Description	Author affiliation: Dept. of Inf. Eng., Padova Univ. (Giani, A.; Grisan, E.; De Luca, M.; Ruggeri, A.)
Abstract	Automatic tracking of blood vessels in images of retinal fundus is an important and non-invasive procedure for the diagnosis of many diseases. Tracking techniques often present a high rate of false positives. This paper presents six methods to discriminate false detections from true positives, each based on a different model of the vessel. They describe a candidate vessel in terms of its average geometric and grayscale properties considered along the full trajectory of the vessel itself. The rationale is that false vessels are caused by the small scale of the tracking algorithm necessary during the tracking phase. Once tracking has been completed, we can gather information from the full vessel trajectory and solve ambiguities that cannot be fixed during tracking. We apply Fisher linear discriminant analysis to these features to get the desired discrimination. Results on 28 images show satisfactory rejection of false positives and better results when using more complex models
Sponsorship	IEEE EMB
Starting Page	4449
Ending Page	4452
File Size	438035
Page Count	4
File Format	PDF
ISBN	1424400325
ISSN	1557170X
DOI	10.1109/IEMBS.2006.260608
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Retina Blood vessels Biomedical imaging Diseases Gray-scale Trajectory Cities and towns USA Councils Image recognition Image analysis
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Improved automated optic cup segmentation based on detection of blood vessel bends in retinal fundus images

Fundus Foveal Localization Based on Vessel Model

Geometric corner extraction in retinal fundus images

A new tool to connect blood vessels in fundus retinal images

Detection of Blood Vessels in Fundus Images of the Retina using Gabor Wavelets

Towards automatic detection of age-related macular degeneration in retinal fundus images

Detecting flash artifacts in fundus imagery

Statistical pattern analysis of blood vessel features on retina images and its application to blood vessel mapping algorithms

Detection of the temporal arcade in fundus images of the retina using the hough transform

Detecting false vessel recognitions in retinal fundus analysis

Similar Documents

Improved automated optic cup segmentation based on detection of blood vessel bends in retinal fundus images

Fundus Foveal Localization Based on Vessel Model

Geometric corner extraction in retinal fundus images

A new tool to connect blood vessels in fundus retinal images

Detection of Blood Vessels in Fundus Images of the Retina using Gabor Wavelets

Towards automatic detection of age-related macular degeneration in retinal fundus images

Detecting flash artifacts in fundus imagery

Statistical pattern analysis of blood vessel features on retina images and its application to blood vessel mapping algorithms

Detection of the temporal arcade in fundus images of the retina using the hough transform

Detecting false vessel recognitions in retinal fundus analysis