A Novel Feature Extraction Approach with VBM 3D ROI Masks on MRI

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dc.contributor.authorOzic, Muhammet Usame
dc.contributor.authorOzsen, Seral
dc.contributor.authorEkmekci, Ahmet Hakan
dc.date.accessioned2020-03-26T19:33:34Z
dc.date.available2020-03-26T19:33:34Z
dc.date.issued2017
dc.departmentSelçuk Üniversitesien_US
dc.descriptionInternational Conference on Medical and Biological Engineering in Bosnia and Herzegovina (CMBEBIH) -- MAR 16-18, 2017 -- Sarajevo, BOSNIA & HERCEGen_US
dc.description.abstractAlzheimer's disease is a neurological disorder that usually starts with aging. Alzheimer's disease is a serious health and economic burden on governments, along with an increase in elderly population in developed and developing countries. There is no known cause of this disease and there is no treatment. For this reason, early diagnosis of the disease, socioeconomic and psychological outputs and medical treatments are still a hot topic investigated in the world. Magnetic Resonance Imaging is one of the medical imaging techniques that show the progression of Alzhiemer in brain. Brain deterioration and volume loss of the disease first begins with memory regions and then spreads to other brain regions. If atrophy is observed and detected by manual methods, it may not be seen due to user dependency, operator error and inexperience. For these reasons, automatic, numerical and atlas-based methods are being developed for the observation and capture of neurological diseases. In this study, 99 Alzheimer patients and 99 normal control MR images were analyzed using Voxel Based Morphometry, one of the numerical methods of atrophy observations in Magnetic Resonance Imaging. Losses in the brain were then produced as three-dimensional binary masks. Using these masks, normalized segmented, modulated normalized segmented, and normalized images that were stripped from the non-brain structures were masked. Histogram based first order statistical features were extracted in the masked areas. The efficany of this technique was statistically compared between Alzheimer's and normal control. MR images have been downloaded freely from the OASIS database.en_US
dc.description.sponsorshipIEEE Bosnia & Herzegovina Sect, IEEE Croatia Sect, Bosnia & Herzegovina Med & Biol Engn Soc, Oracle Bosnia & Herzegovina, Racunari d o o Banja Luka, Infostudio doo Sarajevo, Verlab doo Sarajevo, Privredna banka dd Sarajevo, Symphony Sarajevo, Erkona doo Sarajevo, Bosnalijek dd Sarajevo, Ministarstvo obrazovanje Nauku Mlade Kantona Sarajevo, Trobe Univ, Biosistemi BiH doo Sarajevo, Phoenix Pharma, Medic BH, BBI Centar Sarajevo, FDS, Coca Cola, Klas dd Sarajevo, BioIRC, D Med Healthcareen_US
dc.description.sponsorshipCoordinatorship of Selcuk University's Scientific Research ProjectsSelcuk Universityen_US
dc.description.sponsorshipThis work is supported by the Coordinatorship of Selcuk University's Scientific Research Projects. There is no conflict of interest between authors.en_US
dc.identifier.doi10.1007/978-981-10-4166-2_80en_US
dc.identifier.endpage530en_US
dc.identifier.isbn978-981-10-4166-2; 978-981-10-4165-5
dc.identifier.issn1680-0737en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage523en_US
dc.identifier.urihttps://dx.doi.org/10.1007/978-981-10-4166-2_80
dc.identifier.urihttps://hdl.handle.net/20.500.12395/34744
dc.identifier.volume62en_US
dc.identifier.wosWOS:000462537100080en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSPRINGER-VERLAG SINGAPORE PTE LTDen_US
dc.relation.ispartofPROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MEDICAL AND BIOLOGICAL ENGINEERING 2017 (CMBEBIH 2017)en_US
dc.relation.ispartofseriesIFMBE Proceedings
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectAlzhiemer Diseaseen_US
dc.subjectMRen_US
dc.subjectFirst Order Statisticen_US
dc.subjectVoxel Based Morphometryen_US
dc.subjectFeature Extractionen_US
dc.titleA Novel Feature Extraction Approach with VBM 3D ROI Masks on MRIen_US
dc.typeConference Objecten_US

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