Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/23646
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Loizou, Christos P. | - |
dc.contributor.author | Pattichis, Constantinos S. | - |
dc.contributor.author | Seimenis, Ioannis | - |
dc.contributor.author | Pantziaris, Marios | - |
dc.date.accessioned | 2021-11-16T06:01:15Z | - |
dc.date.available | 2021-11-16T06:01:15Z | - |
dc.date.issued | 2010-01-22 | - |
dc.identifier.citation | 9th International Conference on Information Technology and Applications in Biomedicine, 2009, 4-7 November, Larnaka, Cyprus | en_US |
dc.identifier.isbn | 9781424453795 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14279/23646 | - |
dc.description.abstract | In this study the value of magnetic resonance image (MRI) shape and texture analysis was assessed in multiple sclerosis (MS) subjects, both in differentiating between normal or normal appearing and abnormal tissue and in assessing disease onset. Shape and texture analysis was carried out in normal brain white matter and lesions detected in transverse sections of T2-weighted magnetic resonance (MR) images acquired from 22 symptomatic untreated subjects. All detected brain lesions were manually segmented by an experienced MS neurologist and confirmed by a radiologist. The results showed that there was no significant difference for most of the shape features and for all of the texture features between MS lesions at 0 and 6-12 months. For some texture features there was significant difference between normal or normal appearing tissue and MS lesions at 0 and 6-12 months. Further research with more subjects is required for computing shape and texture features that may provide information for better and earlier differentiation between normal tissue and MS lesions. | en_US |
dc.format | en_US | |
dc.language.iso | en | en_US |
dc.rights | © IEEE | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | MRI | en_US |
dc.subject | Multiple sclerosis | en_US |
dc.subject | Shape features | en_US |
dc.subject | Texture analysis | en_US |
dc.title | Quantitative analysis of brain white matter lesions in multiple sclerosis subjects | en_US |
dc.type | Conference Papers | en_US |
dc.collaboration | Intercollege | en_US |
dc.collaboration | University of Cyprus | en_US |
dc.collaboration | Ayios Therissos Medical Diagnostic Center | en_US |
dc.collaboration | Cyprus Institute of Neurology and Genetics | en_US |
dc.subject.category | Medical Engineering | en_US |
dc.country | Cyprus | en_US |
dc.subject.field | Engineering and Technology | en_US |
dc.publication | Peer Reviewed | en_US |
dc.relation.conference | IEEE International Conference on Information Technology and Applications in Biomedicine | en_US |
dc.identifier.doi | 10.1109/ITAB.2009.5394340 | en_US |
dc.identifier.scopus | 2-s2.0-77949595545 | - |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/77949595545 | - |
cut.common.academicyear | 2009-2010 | en_US |
item.openairecristype | http://purl.org/coar/resource_type/c_c94f | - |
item.openairetype | conferenceObject | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | none | - |
item.languageiso639-1 | en | - |
item.fulltext | No Fulltext | - |
crisitem.author.dept | Department of Electrical Engineering, Computer Engineering and Informatics | - |
crisitem.author.faculty | Faculty of Engineering and Technology | - |
crisitem.author.orcid | 0000-0003-1247-8573 | - |
crisitem.author.parentorg | Faculty of Engineering and Technology | - |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
CORE Recommender
SCOPUSTM
Citations
12
checked on Mar 14, 2024
Page view(s)
249
Last Week
1
1
Last month
2
2
checked on Nov 27, 2024
Google ScholarTM
Check
Altmetric
This item is licensed under a Creative Commons License