Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/12532
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dc.contributor.authorLoizou,  Christos P.-
dc.contributor.authorPapacharalambous, Christos-
dc.contributor.authorSamaras, Giorgos-
dc.contributor.authorKyriacou, Efthyvoulos-
dc.contributor.authorKasparis, Takis-
dc.contributor.authorPantziaris, Marios-
dc.contributor.authorEracleous, Eleni-
dc.contributor.authorPattichis, Constantinos S.-
dc.date.accessioned2018-08-02T11:41:44Z-
dc.date.available2018-08-02T11:41:44Z-
dc.date.issued2017-11-10-
dc.identifier.citation30th IEEE International Symposium on Computer-Based Medical Systems, 2017, Thessaloniki, Greece, 22-24 Juneen_US
dc.identifier.issn2372-9198-
dc.description.abstractDuring a human brain MRI acquisition the resulting image is formed out of 2D slices. The slices must then be aligned and reconstructed to provide a 3-dimensional (3D) visualization of the brain volume. We propose in this work, an integrated system for the register ion and 3D reconstruction of DICOM MRI images and lesions of the brain acquired from multiple sclerosis (MS) subjects at two different time intervals (time 0 (T0) and time 1 (T1)). The system facilitates the follow up of the MS disease development and will aid the doctor to accurately manage the follow up of the disease. It involves a 6-stage analysis (preprocessing, lesion segmentation, registration, 3D reconstruction, volume estimation and method evaluation), as well as module quantitative evaluation of the method. The system was evaluated based on one MRI phantom and one DICOM MRI image of the brain. The accuracy of the proposed registration and reconstruction (- / -) method was 78.5%/97.2% and 95.4%/95.8% for the phantom and the MRI images respectively. These preliminary results provide evidence that the proposed system could be applied in future in the clinical practice.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.rights© 2017 IEEE.en_US
dc.subject3D-Reconstructionen_US
dc.subjectMagnetic Resonance Imagingen_US
dc.subjectMultiple sclerosis diseaseen_US
dc.titleBrain Image and Lesions Registration and 3D Reconstruction in Dicom MRI Imagesen_US
dc.typeConference Papersen_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationFrederick Universityen_US
dc.collaborationAyios Therissos Medical Diagnostic Centreen_US
dc.collaborationUniversity of Cyprusen_US
dc.subject.categoryComputer and Information Sciencesen_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.subject.categoryMEDICAL AND HEALTH SCIENCESen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.relation.conferenceIEEE International Symposium on Computer-Based Medical Systemsen_US
dc.identifier.doi10.1109/CBMS.2017.53en_US
cut.common.academicyear2017-2018en_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.cerifentitytypePublications-
item.languageiso639-1en-
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.parentorgFaculty of Engineering and Technology-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers
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