Retina fundus image mask generation using pseudo parametric modeling technique

This paper discusses a new pseudo modeling technique for the generation of retina fundus image (RFI) mask. The model coefficients necessary for the generation of the mask has been estimated from the synaptic weights of real-valued neural network. Performance analysis of the newly proposed three st...

Full description

Bibliographic Details
Main Authors: Aibinu, Abiodun Musa, Salami, Momoh Jimoh Emiyoka, Shafie, Amir Akramin
Format: Article
Language:English
Published: IIUM Press 2010
Subjects:
Online Access:http://irep.iium.edu.my/1774/1/FUNDUS_MASK.pdf
_version_ 1796874824363016192
author Aibinu, Abiodun Musa
Salami, Momoh Jimoh Emiyoka
Shafie, Amir Akramin
author_facet Aibinu, Abiodun Musa
Salami, Momoh Jimoh Emiyoka
Shafie, Amir Akramin
author_sort Aibinu, Abiodun Musa
collection IIUM
description This paper discusses a new pseudo modeling technique for the generation of retina fundus image (RFI) mask. The model coefficients necessary for the generation of the mask has been estimated from the synaptic weights of real-valued neural network. Performance analysis of the newly proposed three step technique has been evaluated using DRIVE databases and other RFI obtained from other sources. he accuracy obtained by the application of the proposed technique on RFI contained in the DRIVE database varies between 99.62% and 99.97%.
first_indexed 2024-03-05T22:29:59Z
format Article
id oai:generic.eprints.org:1774
institution International Islamic University Malaysia
language English
last_indexed 2024-03-05T22:29:59Z
publishDate 2010
publisher IIUM Press
record_format dspace
spelling oai:generic.eprints.org:17742012-03-10T12:31:12Z http://irep.iium.edu.my/1774/ Retina fundus image mask generation using pseudo parametric modeling technique Aibinu, Abiodun Musa Salami, Momoh Jimoh Emiyoka Shafie, Amir Akramin TK5101 Telecommunication. Including telegraphy, radio, radar, television This paper discusses a new pseudo modeling technique for the generation of retina fundus image (RFI) mask. The model coefficients necessary for the generation of the mask has been estimated from the synaptic weights of real-valued neural network. Performance analysis of the newly proposed three step technique has been evaluated using DRIVE databases and other RFI obtained from other sources. he accuracy obtained by the application of the proposed technique on RFI contained in the DRIVE database varies between 99.62% and 99.97%. IIUM Press 2010 Article PeerReviewed application/pdf en http://irep.iium.edu.my/1774/1/FUNDUS_MASK.pdf Aibinu, Abiodun Musa and Salami, Momoh Jimoh Emiyoka and Shafie, Amir Akramin (2010) Retina fundus image mask generation using pseudo parametric modeling technique. IIUM Engineering Journal, 11 (2). pp. 163-177. ISSN 1511-788X http://www.iium.edu.my/ejournal/home2010/index.php/iiumej/article/view/31
spellingShingle TK5101 Telecommunication. Including telegraphy, radio, radar, television
Aibinu, Abiodun Musa
Salami, Momoh Jimoh Emiyoka
Shafie, Amir Akramin
Retina fundus image mask generation using pseudo parametric modeling technique
title Retina fundus image mask generation using pseudo parametric modeling technique
title_full Retina fundus image mask generation using pseudo parametric modeling technique
title_fullStr Retina fundus image mask generation using pseudo parametric modeling technique
title_full_unstemmed Retina fundus image mask generation using pseudo parametric modeling technique
title_short Retina fundus image mask generation using pseudo parametric modeling technique
title_sort retina fundus image mask generation using pseudo parametric modeling technique
topic TK5101 Telecommunication. Including telegraphy, radio, radar, television
url http://irep.iium.edu.my/1774/1/FUNDUS_MASK.pdf
work_keys_str_mv AT aibinuabiodunmusa retinafundusimagemaskgenerationusingpseudoparametricmodelingtechnique
AT salamimomohjimohemiyoka retinafundusimagemaskgenerationusingpseudoparametricmodelingtechnique
AT shafieamirakramin retinafundusimagemaskgenerationusingpseudoparametricmodelingtechnique