Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/23616
DC FieldValueLanguage
dc.contributor.authorGregoriou, Charalambos-
dc.contributor.authorLoizou, Christos P.-
dc.contributor.authorGeorgiou, Andreas-
dc.contributor.authorPantzaris, Marios C.-
dc.contributor.authorPattichis, Constantinos S.-
dc.date.accessioned2021-11-11T13:01:41Z-
dc.date.available2021-11-11T13:01:41Z-
dc.date.issued2021-09-
dc.identifier.citation19th International Conference on Computer Analysis of Images and Patterns, 2021, 28-30 September, Virtual Eventen_US
dc.identifier.isbn978-3-030-89128-2-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/23616-
dc.description.abstractIn the course of a human brain acquisition, which is acquired by a magnetic resonance imager (MRI), two-dimensional (2D) slices of the brain are captured. These have to be aligned and reconstructed to a three-dimensional (3D) volume, which will better assist the doctor in following up the development of the disease. In this study, a 3D reconstruction integrated system for MRI brain multiple sclerosis (MS) lesion visualization is proposed. Brain MRI images from 5 MS subjects were acquired at four diffident consecutive time points (TP1-TP4) with an interval of 6–12 months. MS lesions were manually segmented by an expert neurologist and semi-automatically by a system and reconstructed in a brain volume. The proposed system assists the doctor in following up the MS disease progression and provides support to better manage the disease. The proposed system includes a 5-stage investigation (pre-processing, lesion segmentation, 3D reconstruction, volume estimation and method evaluation), as well as a module for the quantitative evaluation of the method. Twenty MRI images of the brain were used to evaluate the proposed system. Results show that the 3D reconstruction method proposed in this work, can be used to differentiate brain tissues and recognize MS lesions by providing improved 3D visualization. These preliminary results provide evidence that the proposed system could be applied in the future in clinical practice given that it is further evaluated on more subjects.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.rights© Springeren_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectMagnetic resonance imagingen_US
dc.subjectMultiple sclerosisen_US
dc.subject3D lesions reconstructionen_US
dc.subjectIntegrated systemen_US
dc.titleA Three-Dimensional Reconstruction Integrated System for Brain Multiple Sclerosis Lesionsen_US
dc.typeConference Papersen_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationCyprus Institute of Neurology and Geneticsen_US
dc.collaborationUniversity of Cyprusen_US
dc.subject.categoryMedical Engineeringen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.relation.conferenceInternational Conference on Computer Analysis of Images and Patternsen_US
dc.identifier.doi 10.1007/978-3-030-89128-2_26en_US
cut.common.academicyear2021-2022en_US
dc.identifier.spage266en_US
dc.identifier.epage276en_US
item.grantfulltextnone-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.openairetypeconferenceObject-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0003-1247-8573-
crisitem.author.parentorgFaculty of Engineering and Technology-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
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