Detection and Evaluation of Activation Instances as Change Points in Functional Mr Images
| dc.contributor.author | Candemir C. | |
| dc.contributor.author | Oguz K. | |
| dc.contributor.author | Korukoglu S. | |
| dc.contributor.author | Gonul A.S. | |
| dc.date.accessioned | 2023-06-16T15:00:55Z | |
| dc.date.available | 2023-06-16T15:00:55Z | |
| dc.date.issued | 2018 | |
| dc.description | Aselsan;et al.;Huawei;IEEE Signal Processing Society;IEEE Turkey Section;Netas | en_US |
| dc.description | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 2 May 2018 through 5 May 2018 -- 137780 | en_US |
| dc.description.abstract | Change point analysis is an efficient method for understanding the unexpected behavior of the data used in many different disciplines including medical imaging. It is important to find the instances the activations occur as much as finding the activation areas in the analysis of functional magnetic resonance imaging (fMRI). Change point detection algorithms can be used to find the activation instances. In this study, a regression based point detection method is proposed to find the activation instances in fMRI experiments. The proposed method is applied to a fMRI experiment which includes a motor task. A linear based evaluation method is also proposed. The analyses show that the activations are in accordance with the established methods in the literature. © 2018 IEEE. | en_US |
| dc.identifier.doi | 10.1109/SIU.2018.8404273 | |
| dc.identifier.isbn | 9.78E+12 | |
| dc.identifier.scopus | 2-s2.0-85050791144 | |
| dc.identifier.uri | https://doi.org/10.1109/SIU.2018.8404273 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14365/3607 | |
| dc.language.iso | tr | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
| dc.relation.ispartof | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Activation detection | en_US |
| dc.subject | Activation time | en_US |
| dc.subject | Change point problem | en_US |
| dc.subject | Functional MRI | en_US |
| dc.subject | Chemical activation | en_US |
| dc.subject | Magnetic resonance imaging | en_US |
| dc.subject | Medical imaging | en_US |
| dc.subject | Signal processing | en_US |
| dc.subject | Activation detection | en_US |
| dc.subject | Activation time | en_US |
| dc.subject | Change point detection | en_US |
| dc.subject | Change-point analysis | en_US |
| dc.subject | Change-point problem | en_US |
| dc.subject | Functional magnetic resonance imaging | en_US |
| dc.subject | Functional MRI | en_US |
| dc.subject | Point detection | en_US |
| dc.subject | Activation analysis | en_US |
| dc.title | Detection and Evaluation of Activation Instances as Change Points in Functional Mr Images | en_US |
| dc.title.alternative | Fonksiyonel Mr Görüntülerinde Aktivasyon Anlarinin De?isim Noktalari ile Belirlenmesi ve De?erlendirilmesi | en_US |
| dc.type | Conference Object | en_US |
| dspace.entity.type | Publication | |
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| gdc.description.departmenttemp | Candemir, C., Uluslararasi Bilgisayar Enstitusu, Ege Universitesi, Izmir, 35100, Turkey; Oguz, K., Bilgisayar Muhendisli?i Bolumu, Izmir Ekonomi Universitesi, Balçova, Izmir, 35330, Turkey; Korukoglu, S., Bilgisayar Muhendisli?i Bolumu, Ege Universitesi, Izmir, 35100, Turkey; Gonul, A.S., Ege Universitesi Tip Fakultesi, Psikiyatri ABD., Izmir, Turkey | en_US |
| gdc.description.endpage | 4 | en_US |
| gdc.description.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| gdc.description.scopusquality | N/A | |
| gdc.description.startpage | 1 | en_US |
| gdc.description.wosquality | N/A | |
| gdc.identifier.openalex | W2825198211 | |
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| gdc.oaire.keywords | activation detection | |
| gdc.oaire.keywords | functional MRI | |
| gdc.oaire.keywords | change point problem | |
| gdc.oaire.keywords | activation time | |
| gdc.oaire.popularity | 1.0783119E-9 | |
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| gdc.virtual.author | Oğuz, Kaya | |
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